quantitative research sociology example

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In This Article Expand or collapse the "in this article" section Quantitative Methods in Sociological Research

Introduction, professional associations.

Data Sources
Data Archives
Statistical Software Packages
Research Design
Survey Research
Categorical Data Analysis
Longitudinal Data Analysis
Structural Equation Modeling
Multilevel Modeling
Causal Inference
Critical Reflections
Mixed Methods
Network Analysis
Training and Other Resources

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Quantitative Methods in Sociological Research by Erin Leahey LAST REVIEWED: 27 July 2011 LAST MODIFIED: 27 July 2011 DOI: 10.1093/obo/9780199756384-0044

Sociology develops, adopts, and adapts a wide variety of methods for understanding the social world. Realizing that this embarrassment of riches can bewilder the newcomer, this entry is intended to guide scholars through some of the main methods used by quantitative social scientists and some of the key resources for learning such methods. Because many sociologists in the United States receive foundational training in multivariate linear regression, this entry focuses on developments that go beyond this topic, including categorical data analysis, structural equation modeling, multilevel modeling, longitudinal data analysis, causal inference, and even network analysis. The recent wave of interest in mixed methods also merits inclusion. A section on critical reflections aims to encourage researchers to be reflective and thoughtful about the approach(es) they choose.

A number of professional associations are open to quantitative methodologists and researchers, including the two ASAs ( American Sociological Association and American Statistical Association ), the Population Association of American (PAA) , for demographers broadly defined, and the American Association for Public Opinion Research (AAPOR) for survey researchers and methodologists.

American Association of Public Opinion Research (AAPOR) .

Founded in 1947, AAPOR is an association of individuals who share an interest in survey research, qualitative and quantitative research methods, and public opinion data. Members come from academia, media, government, the nonprofit sector, and private industry. Meetings are held in even-numbered years.

American Sociological Association (ASA) .

The national professional association for sociologists, ASA serves as a reference for professional, ethical, and pedagogical topics; sponsors nine journals; and hosts an annual meeting.

American Statistical Association (ASA) .

ASA is the world’s largest community of statisticians and the second-oldest professional society in the United States. For 170 years, ASA has supported excellence in the development and dissemination of statistical science. Its members serve in industry, government, and academia, advancing research and promoting sound statistical practice to inform public policy and improve human welfare.

Population Association of America (PAA) .

PAA is a nonprofit organization that promotes research on population issues such as fertility, migration, health, and mortality. PAA sponsors the journal Demography .

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[66.249.64.20|185.66.14.133]
185.66.14.133

Principles of Sociological Inquiry – Qualitative and Quantitative Methods

(28 reviews)

Amy Blackstone, University of Maine

ISBN 13: 9781453328897

Publisher: Saylor Foundation

Language: English

Formats Available

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Learn more about reviews.

Reviewed by Sosanya Jones, Associate Professor, Howard University on 1/31/22

Comprehensiveness rating: 4 see less

The book does a fairly good job of covering a lot of topics in the research design process for both qualitative and quantitative research. I think it could have been more expansive in the coverage and discussion about the role of paradigm, reflexivity, and positionality for qualitative research. I also think that its division between qualitative and quantitative research was a bit antiquated with little nuance and complexity for those who want to conduct mixed methods research.

Content Accuracy rating: 4

I think the coverage of paradigms was limited and there was a lack of complexity when it discussed some topics such as approaches. But overall, most of it was fairly accurate.

Relevance/Longevity rating: 3

I think that it needs to be updated to be more relevant, but overall there are still concepts of importance that are well covered in this text.

Clarity rating: 4

It's fairly simple and easy to read for the most part.

Consistency rating: 4

Some topics are covered more in-depth than others.

Modularity rating: 3

It's a bit dense and strangely formatted. In terms of presentation, I don't think it's very appealing for students, but instructors may enjoy the exercises offered.

Organization/Structure/Flow rating: 3

I think the order and organization could have been more cohesive.

Interface rating: 5

Good interface.

Grammatical Errors rating: 5

Good grammar.

Cultural Relevance rating: 4

I think it could have featured more diverse examples.

Overall, this is a good textbook for beginning researchers, but it may need some supplemental articles for areas that are not covered.

Reviewed by Christina Pratt, Professor, Pace University on 7/25/21

Good basic coverage of interpretive and qualitative methods; explanatory and quantitative methods; mixed methods; scant content on innovative approacheds to online surveys, big data; understanding behavior through smartphones; technology and... read more

Comprehensiveness rating: 3 see less

Content Accuracy rating: 3

Methods content is accurate.

The heteronormativity of examples render the text unfriendly.

The text is written in clear accessible language. The examples neglect attention to diversity, inclusion, and equity.

Consistency rating: 3

The text is consistently biased toward examples representing dominant cultural heteronormativity.

Modularity rating: 4

The modules proceed in a logical progression. Good content on research ethics.

Organization/Structure/Flow rating: 4

Fine level of organization and navigation.

Interface rating: 3

The pdf is easily navigated; the hyperlinks to New Yorker cartoons do not visualize the cartoon captioned in the text. All research questions, case examples, illustrations of concepts carry a dominant cultural heteronormative bias.

Grammatical Errors rating: 4

No errors detected.

Cultural Relevance rating: 3

Heteronormativity in case examples, illustrations, questions, inquiry dominate the text. As such, it is outdated as relevant to structural sources of intersectionality in investigator positionality.

Reviewed by Florencia Gabriele, Adjunct Professor, Massachusetts Bay Community College on 6/29/21

The book would benefit from an index and glossary. The material is easy to find despite lacking an index and the book follows a logical order and the material becomes more complex as the book progress. read more

Content Accuracy rating: 5

I found no errors in the book

Relevance/Longevity rating: 5

The book can be used in any humanities/social science class, not only in sociology

Clarity rating: 5

The book is an excellent source for any principles of research class for high school, community college, or college classes. the book si clear to understand and follow

Consistency rating: 5

The book is consistent and provides a complete overview of what it takes to do research and write a research project/paper for students.

Modularity rating: 5

the book is divided into chapters that are easy to follow and understand and could be divided into smaller sections if needed.

Organization/Structure/Flow rating: 5

The book is organized in a logical manner.

I had not issues using the interface and neither did my students.

I found no grammatical errors

Cultural Relevance rating: 5

The book is inclusive and provides excellent examples

I used the textbook to introduce college methods to a pre-college class of outstanding students who wanted to write a good sample paper to be used in their application essays for college. The book was clear, well organized, and provided great examples. also, it did not overwhelm my students. while it might not be appropriate for a college-upper level class, it is a great introduction on how to do research, how to ask a proper question, how to organize the work and the data, what type of study to do, and how to write a paper.

Reviewed by Kay Flewelling, Adjunct Faculty, University of San Diego on 5/3/21

This is an easy-to-read description and introduction to principles of sociological inquiry. Blackstone is adept at explaining critical social science research terminology as she places these in context with other disciplines. The introduction to concepts is comprehensive, though not overwhelming with details. There is no glossary provided, though the Table of Contents provides some help with navigating through the different chapters.

I found the overall tone to be well managed, and found no errors in her descriptions of sociological concepts and research terminology.

The content was relevant, and timely. As the focus is on research principles, these topics were well-placed within context of seminal theories. If topics become outdated, these could be easily updated.

The strength of this text is the clarity of the prose. The author speaks directly to the reader, and makes research and methodology seem accessible and relevant. Terms are carefully defined and placed in easy-to-access contexts.

The text has a direct tone throughout. Each aspect of the research process is described in a similar, conversational tone.

This text is somewhat modular, but there are numerous points of self-reference that might make it less able to be easily assigned as distinct chapters.

The structure and flow was strong, especially in the early chapters. I found some of the later chapters to be a bit tacked on. For example, there is a chapter on how to consume research that I personally would assign with the chapter on reading literature.

I had no issues with navigation.

The book is clearly written. There were no grammatical errors that I noticed.

The text felt clear and culturally sensitive. If anything, it could have been more explicit to address cultural issues.

Reviewed by Yang Cheng, Assistant Professor, North Carolina State University on 4/2/21

I reviewed the topics such as quantitative methods and qualitative methods, Chapter 2: Linking Methods With Theory, research ethics... The author did contain different topics in this book. If the author could provide more examples of quantitative... read more

Yes, it did accurately described each type of method and its applications in the real world.

It is relevant to the book introduction and title.

It accurately described qualitative and quantitative methods in sociology and provide concrete examples as well. The book could elaborate more on each type of research method. For example, when they introduce the survey method, more content could be illustrated such as how to design a research question for what type of survey method...

The text is internally consistent in terms of terminology such as quantitative methods, measurement, and research design, etc.

The text is easily divisible into smaller reading sections.

The book follows a logical way to present different topics: It introduces why we need research methods, research methods, and then illustrates each type of method, and finally discusses the application in real practice.

The text is free of significant interface issues and I did not observe one.

The text contains no grammatical errors.

Yes, the book is inclusive of a variety of races, ethnicities, and backgrounds.

Reviewed by Antwan Jones, Associate Professor, The George Washington University on 12/16/20

The textbook covers a large amount of material that introduces the reader to research methods. One of the weak points of the book is a lack of discussion on how to conduct a literature review. This information can obviously be supplemented, but it... read more

The material is accurate with no presence of bias – which is great because you can normally tell whether the author of a methods textbook has a partiality for quantitative or qualitative methods. In this book, the author presents the material for all types of methods objectively.

Relevance/Longevity rating: 4

Some of the examples provided are dated, but that is simply an artifact of when the book was written. Professors who decide to use this text should supplement examples included in the book with more contemporary examples that could be used to reinforce the material.

The language is very clear and user-friendly for an undergraduate student with limited exposure to research.

The book is well-structured with similar headings across all chapters.

If an instructor wanted to shuffle some of the content around, the structure of the book would allow for that to occur with ease.

This textbook is organized like other textbooks that I have used for Methods courses. One of the issues that I find with this “standard” organization is that that the reading and understanding research is one of the final chapters, when it really should be one of the first chapters of the book.

Interface rating: 4

I usually do not rely on external content from textbooks in my courses, but I decided to click on a random selection of external links within some of the chapters. Overwhelmingly, the links work and some of the content was highly relevant, but there were links that were broken as well. I mentioned in another section of my review that instructors should supplement this textbook with newer examples. By doing so, it would also remedy this potential textbook flaw.

Very few, minor grammatical errors are present in the book, but none are so egregious that it takes away from the quality (or the readability) of the work.

The examples and content are relevant to national (i.e., American) and international audiences, but more global examples would make the textbook even more culturally sensitive to a demographically changing world.

Research methods is a “bread-and-butter” course for the social sciences, so the context rarely changes. If you are looking for a quality textbook that gives students a solid foundation of the basic tenets of social research, this book will meet your needs.

Reviewed by Linda McCarthy, Professor, Greenfield Community College on 6/29/20

Comprehensiveness rating: 5 see less

I have not reviewed or used other methods books, but this book includes what I would expect. I imagine most students would need more guidance on how to analyze data, whether it be quantitative or qualitative. I appreciate that Blackstone includes the reasoning or the whys and whens of each method, as most students I encounter all are drawn to surveys, even when their research question would not warrant a survey. I liked the inclusion of how to review existing sociological research. I wonder if that would be interesting as part of the opening of the book? At least, the media module? Great to end the book with where we see sociological research being used in the "real world". And, excellent idea- to include a list of "transferable skills"! Students will feel that reading this book is time well spent! I did not see a glossary or an index.

Each chapter provides examples from research and gives citations for all these cited. I did not detect bias.

Research studies referred to are relevant, though some are highlighted more than others, and I was curious about some of those choices. I believe it will not be difficult to update the examples. Some of the examples (such as videos to check out) are pretty dated. For example, a clip from The View from 2011 will seem like ancient history to these students. I wonder if there are ways to better incorporate examples from social media (e.g Tic Tok instead of email)? That may be challenging as it changes so quickly. I like that students are introduced to a variety of sociological resources throughout this book.

I like the tone of the writing; it's easy to follow and friendly. The "technical" terms are explained well and contextualized as to why they are important. Blackstone's tone is personable; I like that she refers to her own experiences in a variety of ways.

Each module has the same Learning Objectives, Key Takeaways, and Exercises. Some of the Exercises are not as strong as others. The author wraps up the book by referring back to the beginning Intro chapter.

I like the modules format. Works for the short attention we all have these days. I would assign a chapter or two from this book to my Intro course.

I liked the order of topics very much. Starting with an intro, then theory, and ethics, before moving into how to start a research project makes sense. I liked how the student is encouraged to "start where they are". Being led through the possibilities of qualitative vs. quantitative, including the different types of field research was helpful and interesting. The order of the chapters made sense to me.

Interface rating: 2

On the PDF version, some tables carried over between pages, as did some of the Key Takeaways sections. Some of the visuals were not visible. Also, I got some 404 messages (the "hilarious video" on page 5, for example), which was disappointing. Also, every time I opened a link, it brought me back to the first page again, and that was frustrating. In fact, it taught me not to open any more links. The New Yorker cartoon links just takes you to a whole lot of them, not the one listed. Why list the Endnotes BIG (2) if they aren't hyperlinked? I don't like the different fonts. I checked out the online version and it is much easier to look at. Can the hyperlinks be set into the text, rather than the whole addresses listed out?

A couple minor grammar issues here and there, including no space between sentences.

In the research ethics section, I would suggest addressing the idea that vulnerable populations have included GLBTQ populations and therefore, sexuality research has been hindered to a certain extent (See Janice Irvine's work). A good variety/diversity of studies is referenced, allowing everyone to "see" themselves" in the book. I love the variety of examples in the "starting where you are" section.

I enjoyed it! I would feel comfortable assigning this book to second year community college students.

Reviewed by Walter Carroll, Professor of Sociology, Bridgewater State University on 6/10/20

This book appears reasonably comprehensive although the absence of coverage on network analysis is a weakness. Some recent textbooks have begun to cover this important approach. I would also have liked to see more coverage on data archives. For example, although the texts refers to materials like Addhealth and the GSS, I did not see mention of the Inter-university Consortium on Political and Social Research (ICPSR). Although I emphasize both quantitative and qualitative aspects in teaching research methods there are topics covered that I would leave out, such as ethnomethodology. I would also liked to have seen information on carrying out Literature Reviews. I may have missed some of these things because of the lack of an index and a glossary. Other reviewers have pointed this out. For me this is a serious problem. As others have also pointed out, the 2012 publication date leads to some dated examples and no opportunity to include more recent examples. I used the pdf version for this review. I would like to see a deailed Table of Contents and an overall Chapter Outline at the beginning of each chapter.

The book seems to be accurate in discussing the material. The author presents the material accurately and in an unbiased way.

The contents were up-up-to date as of 2011-2012, but it needs revision to include more recent research examples and techniques. Although network analysis is not new, it is receiving renewed attention in methods texts. This book does not consider that approach. Although there are many basic underlying principles in research, there are also advances and many new examples of research that ought to be incorporated. Other reviewers have pointed out that instructors could add newer materials and resarch examples. This is true, but given the uneasiness with which undergraduate students approach research methods they often cling to the text as a life-saver and I'd prefer a more recent text.

The writing is accessible and clear. Occasionally there are grammatical errors and odd sentences, but overall Blackstone's writing is approachable.

Yes, the book is internally consistent in terminology and framework.

I differ somewhat from other reviewers on this. Yes, text is modular and sections and chapters can be moved around and reshuffled. However, I think that there is an order to thinking about research so a lot of modularity is not necessarily a big advantage to me. This is especially true in early sections fo the book when the author discusses general issues in methods, such as ethics, sampling, and research design. Actually, I prefer integrating discussions of some of those topics, such as ehtics, into coverage of each type of data gathering.

It is a well-organized text although a detailed table of comments, as I mentioned above, would make the organization more apparent to students early on in the class.

In the pdf version there are interface issues, but this may not be true of the online version.

There are a few, but not many.

The text is culturally senstivie and inclusive. A newer edition with more recent examples of studies in inequality, racial and ethnic issues, and gender would strengthen it.

This is a praiseworthy effort that arose from the author's own experiences and frustrations taking and -- presumably -- teaching research methods. It is accessible and has no major flaws, other than being a little old and lacking a few topics that I emphasize. I, and I think most faculty members, consider cost in adopting texts so it is appealing in that sense. However, there are other reasonably-priced methods texts. If it were updated to say 2017 or so, included more recent examples, and covered a few areas that I emphasize, such as network analysis, I would consider using it. As it stands however, although I like it, I would not use it.

Reviewed by Colleen Wynn, Assistant Professor, University of Indianapolis on 5/27/20

This text is quite comprehensive for an introductory methods course. It nicely covers both quantitative and qualitative methodologies. I appreciate the use of sociological examples both historical and contemporary. Of course, since this edition is from 2012, the current examples are becoming a little outdated in 2020, but still serve as quality examples for students. As other reviewers have pointed out, there is not an index or glossary, though in the online version one can hover over key terms for definitions.

The content appears to be accurate and free from bias. There are some links that are broken, so instructors would need to check these and perhaps provide the current link or a substitute, but as the reference information is provided, this seems possible to do. There are also some editing errors, but the content itself is accurate.

This text uses both more classic examples and ones current to the 2012 publication date. Instructors could easily layer on additional examples in lecture or supplemental reading. The core concepts of research methods do not change very often, and most instructors use a combination of classic and contemporary examples, as this text does. The discussion of experiments in Chapter 12 could use more sociological examples of audit-studies, etc. This would be something instructors would probably want to add and discuss since these studies are used quite frequently in sociological research and their omission is disappointing.

The book is written very clearly and would work well in an undergraduate class. Key terms are bolded and explained, and in the online version, you can hover over them for a brief definition. Each section begins with learning objectives and ends with key takeaways and exercises. This presentation allows students to understand what they should be getting from the section (learning objectives), review that information (key takeaways), and apply their new knowledge (exercises). Instructors can use these to guide their classes, student reading, activities, etc.

The book is very consistent, using the same format for each chapter and subsection. This allows students to reorient before each new topic by reviewing the learning objectives and summarize each section in the key takeaways. This consistency is key as students often perceive methods to be a dry, boring subject.

Individual chapters or even subsections could easily be pulled out and used for other courses. Additionally, it seems possible to reorder some of the chapters, if an instructor would prefer, or to skip one here or there if time or course design warranted. This modular ability is a real strength of the text.

The book is well-organized and follows the same convention of many methods texts. However, if instructors would like to reorganize, the modularity would allow for the reorganization of this content to fit their course. Personally, I would probably move Chapter 14 on reading research earlier in the semester (maybe after Chapter 2) as I like to have students read examples of research alongside the text, and having a foundation of how to read and understand these articles and reports would be useful. But, overall, I think the text is well organized.

The online interface is easy to use. However, the PDF version has tables breaking across pages, figures missing, and the text sometimes changes size and font, which is quite distracting. Additionally, in the PDF there is no table of contents or way to easily navigate within the document. For this reason, I would encourage students to use the online version but download the PDF as a backup.

There are several grammatical errors throughout, but these are relatively minor.

The text uses a variety of diverse examples. The author could include more global examples in future editions if they wanted to add a more global component.

I appreciate there is an open-access methods book for sociology and I look forward to using this book in my future courses. Methods books tend to be quite expensive and it is a class where having the book is crucial for success so I think this is a great option to ensure students have access!

Reviewed by Yvonne Braun, Professor, University of Oregon on 11/27/19

I generally really liked this methods book and can imagine using it in an undergraduate methods course. It covers the main sections that most of us would expect to see in a methods text. The text needs a table of contents with breakdowns by... read more

The book generally seems accurate. I think some of the discussion at times could have more nuance, but I understand and appreciate that the author has kept this methods book concise and focused which may have come at the cost of nuance in some areas.

This is a very relevant text with updated materials and I can imagine using it for a methods course. I really appreciate the focus on mixed methods which tries to move beyond the quantitative and qualitative divide that too often is the focus. It seems it would be relatively easy to update in the future due to the way it is organized.

The author writes very clearly and directly which I imagine would work well for undergraduate students at the introductory level. At times, I can imagine definitions being made more distinct could be useful for students.

The author keeps the book very consistent throughout, and successfully builds on examples and references made in multiple chapters.

The book has multiple levels of modularity. I particularly like that the chapters largely stand on their own so that I can imagine selecting chapters to be used in a different order in my class. Each chapter has multiple modules that seem to keep each section reasonably focused on a particular set of ideas and concepts. A table of contents would really help.

I generally like the organization of the book. It seems organized similarly to other methods books in the field. As noted above, I particularly like that the chapters largely stand on their own so that I can imagine selecting chapters to be used in a different order in my class.

I reviewed the PDF version. In general, I found it easy to navigate. My biggest complaint is the font and spacing issues that I find very distracting and even overwhelming at times. Some of the text, like chapter titles when referenced in text, are larger and in a different font and the spacing feels crowded.

There are a few grammatical errors that another round of edits would easily fix. A few sentences end strangely, and take a second read to understand.

The author does a nice job of aiming to be inclusive in the text with diverse examples.

I look forward to using this book in a future course.

Reviewed by Fatima Sattar, Assistant Professor of Sociology , Augustana College on 7/30/19

The text does a great job covering a range of qualitative and quantitative methods. I did not see an index or glossary. The text would benefit from adding both and/or a list of terms students should be familiar with at the end of each chapter. It is very helpful that key terms are in bold in the text. In a future edition, more recent sociological scholarship on experimental methods and comparative and historical methods would be helpful.

The text appears to be accurate and unbiased as the author discusses strengths and weaknesses of the methods. The only error I noticed was that there were a few links to sources that did not work. The full reference is given so this can be easily found.

There are many relevant and classic examples that undergraduate students will be able to relate to. The narrative/personal style makes the text very accessible.

The author's writing is very clear, making it easy for undergraduates to comprehend. For example, students struggle with abstract concepts, e.g. theory vs. paradigm. The examples given provide clarity for students. There could be some clarification in Chapter 2. In Figure 2.2 the three main sociological theories are mentioned but also listed as paradigms. An explanation of interchangeable terms/complexity could be discussed more. The examples are excellent for giving students a better understanding of theory. The discussion of methods and theory could be elaborated as well (e.g. more examples of macro-micro links, macro forces impinging on the micro-local, research not being about just one of these, micro, meso, or macro).

The book is very consistent. Each section begins with "Learning Objectives" and ends with "Key Takeaways" and "Exercises". Very easy to follow!

I think the sections can be read on their own and assigned when needed.

I would probably reorganize some of the sections in teaching the course, because, for example, I would teach qualitative methods before quantitative methods. Also, the chapter on "Reading and Understanding Social Research" could be linked with "Research Design" to offer students examples earlier in the term to help inspire a project or begin a literature review for a research methods proposal assignment.

Interface is clear.

I did not notice any significant grammar issues.

The text has diverse examples but could expand to include more global research examples.

I would reorganize chapter 12 and 15. Focus group research could fit with applied or evaluation research - so these chapters could be combined. I also think the title of Chapter 12 could be more concrete than just "other methods." Experiments could be discussed earlier in the ethics chapter to offer more balance with ethically questionable experiments with experimental research done for social good/advancing equality. Add more examples of experiment research in sociology (e.g. Pager, 2003).

Reviewed by Rae Taylor, Associate Professor, Loyola University New Orleans on 4/24/19

The text covers all the areas a research methods textbook should, in an easily digestible way. read more

The text covers all the areas a research methods textbook should, in an easily digestible way.

While there are some quirky examples and passages throughout that undergraduates will probably roll their eyes at, the book reads free of bias and certainly accurate.

The content is indeed up-to-date, and will be easy to update as examples become obsolete.

The book does a great job of covering the material in a straightforward, non-intimidating kind of way. In my experience, students are nervous about taking Research Methods (though, not as nervous as Data Analysis), and this text should put them at ease. It is written in a very undergraduate-friendly way (indeed, probably too rudimentary for graduate students), explaining the more complicated concepts in a clear manner.

The book's writing style and layout are very consistent, which should help students navigate what may otherwise be considered dry material. This is a real plus.

This is a major strength of the book. I teach methods in a variety of formats (i.e. full semester, face-to-face, online, 8-weeks) and need a text that is modular. Not only are the chapters organized in a logical order, the individual chapters are modular, allowing a professor to assign sections of a chapter. This is particularly useful for some of the more complex areas, and areas where the professor would have supplemental materials.

The order of the chapters is logical and the individual chapters are also organized in a logical, useful way.

The text appears to be free of any of these problems. I am not sure how different computers or different software may affect this, but I had no interface issues while reading the text at home or at the office.

I did not detect grammatical errors.

I did not find anything to be culturally insensitive or offensive.

I appreciate very much that there is an open textbook option for research methods. There are many of these texts available, many very good, but they are always quite expensive, and often students will not buy them. As this is one text I believe is critical for a class, having the open text option is a wonderful alternative. I reviewed this book looking for things that were important but omitted, but it was comprehensive and current. I was also particularly concerned about the order of topics, but it has a great layout and order to the chapters. Finally, as stated above, I find the modularity to be a major strength.

Reviewed by DeAnn Kalich, Professor and Head, University of Louisiana at Lafayette on 3/31/19

I like the approach used here because I agree qualitative and quantitative methods are complementary rather than competing. Many methods books divide these out rather than synthesizing; I find that Blackstone has done an excellent job of weaving these complementary methodologies together in her use of real research examples throughout the text. Chapter 3 is excellent not only as an introduction to ethics in research on human subjects, but on the history and purpose of IRB as well. There is no glossary as other reviewers have noted, but I honestly don't mind that. I have seen students rely on such items exclusively and therefore to not read the context or elaboration in the text and to subsequently understand the definition poorly. An index would be nice, but possibly difficult to tie to pages since the formats shift in differing versions (pdf v. online, for example).

The content is accurate and unbiased as it pertains to research methods per se. The presentation of the content, on the other hand, is not error free, and could use some finer editing. For example, there are missing words throughout the first chapter – this should be caught and fixed; it will undermine a student’s value placed upon the book assigned by their instructor. There are also broken links throughout the book but especially heavy in the first two chapters: 1.2 Exercise 3 video link doesn’t work; 1.3 Exercise 2 link is bad for ASA jobs; video clip links don't work in chapters 1, 2, 3.

The book uses both classic and contemporary research studies as excellent examples to further understanding of content. It will be relevant for the future with very little need to update due to obsolescence. I like the arrangement of the content and think it will flow naturally for a research methods class.

This text is one of the most lucid for students I have ever read. Many methods books are written with so much jargon that they hinder rather than help, especially undergraduate students. This text, on the other hand, provides easy to understand examples that are of interest to today's students, especially in North American undergraduate sociology programs.

The text is internally consistent and is well organized. The PDF version, however, is difficult to follow because the page breaks occur at inconvenient places (in the middle of a table or graph, or citation information).

In particular, the subsections in each chapter are divided into small reading sections that can easily be assigned at different points in the course. It is easily realigned to match the subunits of a course you may already teach without being difficult to do.

As stated above, the text is very well organized. It is logically ordered, and topics align closely to those found in most methods texts, but without unnecessary detail or extraneous fluff. Only one non-logical portion exists: Chapter 4 starts with a reference to preceding questions and BethAll and neither are in my version of the book. Not sure what is missing.

Again, the PDF format of the text has more interface issues due to the page-break locations that could be confusing to a student reader especially. Other features such as links to external cites like the ASA can confuse or distract a reader when the promised link is no longer a working link. A regular (twice yearly?) check of all such links is highly recommended.

Grammar is error free but copy editing is not. It is clear that the author is capable of executing complex sentences without grammar errors, but, there are words that are completely absent throughout the text that are obviously proof-reading related. It is highly recommended that there be a copy editor for this text.

The text is inclusive and not offensive or culturally insensitive. It makes use of examples that include a variety of backgrounds and characteristics (race/ethnicity, gender, SES).

Chapter 15 is excellent for undergraduate sociology programs that require a research methods sequence for majors. Some of these students will go on to graduate work, but many will not, and this chapter provides real world information on careers using sociology and research methods that is useful and accurate.

Reviewed by Sarah Quick, Associate Professor of Anthropology and Sociology, Cottey College on 8/2/18

This book, in general, is comprehensive in that it covers research questions, the research process and design types, major methods or data collection strategies, and ethics from a sociological perspective. It is very accessible for undergraduate readers, but also assumes they are sociology students (as the title would suggest). Nevertheless, as one of the few open access methods books available, I have opted to use this book in a more interdisciplinary research methods course; and I am a cultural anthropologist—so I don’t see it as comprehensive if you include a wider disciplinary breadth. Even when other disciplines are included to locate their differences in framing research questions (chapter 4), anthropology is missing. Nevertheless, anthropology is definitely covered in the field research chapter (chapter 10), and I found this chapter to have a lot of depth in considering field notes and the next steps towards analysis. However, this chapter did not include anything on the more quantitative forms of observation used by some social scientists (even anthropologists). Finally, there could be at least a list or a list of resources for those other missing methods that the author implies exist in the Other Methods chapter (Ch 12).

As previous reviews have noted, there is no index. So, for example, a reader would not necessarily know that there’s a section on content analysis in the Unobtrusive Research chapter (chapter 11) unless reading that section directly. However, if you use the pdf. version instead of the online version, you may search it easily enough with key words/control f.

Part of the comprehensiveness or uniqueness of the text is the inclusion of the three final chapters on broader questions related to research (or why an informed research perspective may help you more broadly). One covers writing/publishing issues, another on how to read research papers critically as well as interpret others’ critiques/interpretations; and the final chapter really addresses the undergraduate audience by highlighting how research appears in jobs that may not be so obviously related to sociology. I imagine these chapters would be really helpful for a specifically-sociology methods course, but I’m not sure I will use all of them for the course I will be teaching.

Overall, a previous reviewer caught many more problems (although some of them were semantic rather than accuracy issues). But, I would agree with this reviewer on the paradigm vs. theory sections. I think these distinctions could be posed with more nuance, within a more interdisciplinary understanding/approach to paradigms and theory. I would agree with this reviewer that the paradigms and the theoretical umbrellas proposed are more overlapping than the author indicated. Also inaccurate is to not mention animal research in the non-human section and to not link this with ethical questions in the social sciences. Although perhaps uncommon in sociology, human-animal interaction studies are a growing area of interest that should not be excluded and require a nod to ethical concerns

The text does use relatively recent examples alongside classic studies, which I think is a good strategy. Nevertheless, some things (like the current president, the reliance/influence of social media) could be updated further.

Overall, the text is written very accessibly, and one of the reasons I plan to use it.

I did not notice any consistency issues although other reviewers did.

The book does reference previous sections/chapters quite a bit, but each section generally stands on its own well enough so that it could be sectioned out in different ways.

Overall the book flows well, and I especially appreciate the resource links and discussion questions at the end of each section.

Depending on whether you use the pdf vs. the online link, you will have a different experience. The online version, at first, seems easier to read until you get to a reference, then your reading is interrupted by the citation/citations, which can make the reading quite disjointed. In the pdf version these citations are in numbered notes that do not link, and the endnotes appear at the end of these sections. Neither interface is completely ideal.

Also, I appreciated the links to additional resources, but at least one link didn’t work (http://www.rocketboom.com/rb_08_jun_04/).

I did not find any grammatical errors.

Overall, the cultural relevance seems fine for a sociology course, although I would like more examples of cultures/studies outside the U.S., since that’s what I’m more used to as an anthropologist.

As noted above, I plan to use this book supplemented by many other chapters/articles for a Qualitative Methods course I will be teaching, one that is not housed in any one discipline. Because of the book’s accessibility (writing and price), even with the problems noted above, I will use it.

Reviewed by Bernadine Brady, Lecturer, National University of Ireland, Galway on 2/1/18

This text provides a very comprehensive introduction to Research Methods. In my opinion, it covers much of the content required on an undergraduate social science methods course, and is of particular value for sociology students. The value of the book is in providing a comprehensive primer to help students to understand why and how research is undertaken. The reader can then supplement this knowledge with more in-depth texts as required. For example, the text is a little light on the philosophical foundations of qualitative and quantitative research (which may be seen as a strength or a weakness depending on your perspective!). No index or glossary are provided.

The book content was accurate and no errors were noted. The language and content was unbiased.

This book feels like it was written by a young person and draws on a range of examples and case studies that have contemporary relevance, which will have appeal for a lot of students. There are some specific content that will date - for example, in Chapter Four it is stated that Barack Obama is president. However, this content can be easily updated meaning that the book will remain relevant for a long period of time.

The main strength of the book, in my opinion, is its clarity. It is written in a very accessible style and the author does a really good job of explaining difficult concepts and research jargon in a very clear way. Practical examples are used throughout to demonstrate key concepts.

The text appears to be consistent in terms of its terminology and framework.

This book can be easily divided into sections. Each chapter has a number of sub-sections, with clear learning objectives and takeaway messages included. I plan to use specific chapters of the book as recommended reading in a number of sessions of my research methods course. It should be noted that qualitative and quantitative methods are considered in tandem which may not lend itself to the teaching of modules dedicated to one approach only.

The structure of the book makes sense, with the topics organised in a logical, clear fashion.

The book is available in both Pdf and online format. The interface is clear and easy to navigate but there are some aberrations with regard to the formatting of in-text references in the online version. This is not a deal breaker - the Pdf version can be used if this is off-putting.

I did not have any issues with regard to grammar.

The content is probably quite North American in focus but has broader cultural applicability. A variety of examples are used that are inclusive of a variety of races, ethnicity and backgrounds.

In her preface, the author says that she was inspired to write this book from her experience as a student and having ideas about how she would like to be taught. The book is approached in this spirit and is written with the student in mind. There is a strong emphasis on making sociology and social research relevant to the students everyday life and interests. The author does a good job of de-mystifying complex concepts. As a result, it is a very accessible text that will appeal to students both at undergraduate and postgraduate levels. I will be recommending this text for my courses.

Reviewed by Joanna Hunter, Assistant Professor, Radford University on 2/1/18

There isn't a glossary at the end of the book, or a list of bolded terms with definitions at the end of each chapter, which would greatly improve its navigability. My experience is that when students see a bolded term, they expect a list of them somewhere with definitions included. There is no index available. That said, the book is a comprehensive introductory textbook about research methods in sociology. The choice to tease out the differences between qualitative and quantitative interviewing is an interesting one, and one that is different from the approach in almost all other methods textbooks I am familiar with. I worry this would confuse students as they tend to want to draw clear lines between qualitative and quantitative methodologies, particularly at the introductory level.

There are a few small inconsistencies as noted in prior reviews, but the book is generally accurate. I will focus the bulk of my comments here on the chapter/section on public sociology. This text focuses very specifically on public sociology, but gives short shrift to policy sociology, with only a short paragraph on page 176 covering it. Particularly as we move into a paradigm where students expect that the skills they learn from our courses and programs will lead them directly to employment opportunities, this is a problematic omission.

Methodology changes comparatively slowly than other subject areas within sociology. That said, several of the examples given should be updated to reflect current realities.

Writing is generally clear, concise, and straightforward. That said, some of the terms used different than the terms I'm familiar with from other textbooks on the subject, which would require a bit of a shift in teaching style. That is not necessarily a bad thing, but could be a barrier to adopting the textbook.

The book is relatively consistent, but there are some editorial errors wherein certain tables/typologies use one set of terms and then other set uses a slightly different set of terms, which could be confusing for students.

The book is organized into modules that could be separated, but not without some work on the part of the instructor. At several points, there are calls back to previous chapters/modules that would need to be edited or addressed by an instructor if they were attempting to only use one (or several) modules.

Topics are organized well, but I found the insistence of including a learning objective for each and every small section to be a bit overbearing.

There are some issues with tables/charts not paginating correctly in the PDF format, and the HTML version sometimes returned a 404 error when using the 'back' button on my browser (Safari). There is no TOC in the PDF version.

No major grammatical errors.

No issues with cultural relevance.

Overall, a useful resource that could be modified to fit a variety of different courses.

Reviewed by Jessica Ganao, Associate Professor, North Carolina Central University on 2/1/18

The text covers all areas and ideas of the subject appropriately and provides an effective index and/or glossary. I especially like Chapter 14, as this something that I often assume students understand but they really do struggle with it. read more

Content is accurate, error-free and unbiased.

Content is up-to-date, but not in a way that will quickly make the text obsolete within a short period of time. The text is written and/or arranged in such a way that necessary updates will be relatively easy and straightforward to implement. I like the fact that is a generic social science methods book because I can then add examples relevant to my field (criminal justice), but at the same time I adjunct at other universities in different disciplines so it will allow me to offer examples in those areas as well.

The text is written in lucid, accessible prose, and provides adequate context for any jargon/technical terminology used. Indeed, this is very important as to make the content accessible to all students.

The text is internally consistent in terms of terminology and framework.

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). I agree, the text reads like a real book, which makes it easy to divide the content into sections for students and to assign sections for different class activities.

The topics in the text are presented in a logical, clear fashion. The book flows like all the other research texts I have used. It is very consistent with the leading research texts.

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader.

The text is not culturally insensitive or offensive in any way.

I really am excited about this option for my students! I cannot believe a book of this quality is free!

Reviewed by Molly Dondero, Assistant Professor, American University on 2/1/18

Overall, I found the book to be fairly comprehensive. It touches on the main topics covered in an undergraduate sociological methods course, as well as some additional topics such as the chapter on “Research Methods in the Real World.” In general, I found the later chapters to be more comprehensive than the earlier ones. Some of concepts presented in the early chapters would benefit from additional depth. For example, I think the text would benefit from a stronger focus on how theory guides research and particularly, the link between theory, research questions, and hypotheses. The section on research questions could also be expanded. For these reasons, I would likely supplement the text with additional readings and/or lecture to expound on some of these key concepts.

The book lacks a glossary or index, which would be quite helpful.

I found the book to be generally accurate. As explained in my comment above, the explanations of some concepts could be improved by going into more depth, but they are not inaccurate as is.

The content is up-to-date. As is common, many of the examples provided will likely benefit from updating in the next several years, but the core material has longevity.

The writing is one of the main strengths of the text. The writing is clear and engaging. Blackstone defines key terms and concepts in a largely jargon-free fashion. This makes the text well-suited to an undergraduate audience of Sociology majors and non-majors alike.

The text is consistent in terminology and framework. Throughout the book, Blackstone makes references to concepts and examples discussed in previous sections. This adds to the overall consistency of the text and helps students to see how concepts connect.

Chapters are divided into short sections that can be easily assigned to and digested by students. The “Key Takeaways” sections at the end of each chapter are particularly helpful.

The organization of the book, particularly in the first four chapters, was not intuitive to me. If I adopt the text, I will likely teach the chapters out of order. For example, I would likely reverse the order of Chapters 2 and 3 (“Linking Theory and Methods” and “Research Ethics”).

There are no figures in the PDF version. I did not note any other significant interface issues.

Grammatical Errors rating: 3

There are no significance grammar issues. However, there are sentences that are cut-off throughout the text (e.g. pp.52, 56, 62, 64 in the PDF version). These sentences all seem to be missing references to other sections of the book. The text would benefit from an additional round of editing to correct these issues.

The language is culturally relevant and inclusive. The author (understandably) draws most heavily on examples from her own research, but overall the examples provided throughout the text are inclusive of a range of diverse backgrounds.

Reviewed by Susan Calhoun-Stuber, Chair, Dept. of Sociology and Anthropology, Colorado State University Pueblo on 2/1/18

The book is a comprehensive social science research methods text. It includes expected topics and some additional attention to some subjects. There is not index or glossary but the chapter titles would guide readers to appropriate topic areas. read more

The author presents a balanced view of different methodological approaches and theoretical perspectives in the social sciences.

There's little problem with current content as the information that needs to be kept current, examples from published research, could easily be updated.

One of the author's stated objectives in writing the text was accessibilty and she has accomplished this goal. Overall, the presentation, including examples, explanations, and definition, is straightforward and clear. The author's style will facilitate student understanding.

The text is internally consistent, within and across chapters.

The text's modularity is a strength. The sub-sections or units within each chapter could easily be reorganized within a different overarching course structure without detracting from the readers' learning or comprehension. Similarly, units within chapters could be re-aligned and chapters could be combined or rearranged with relative ease.

There is a clear logic to the book's organization. The key points (to be covered) and key takeaways at the opening and closing of sections, respectively aid the reader in focusing on core concepts. Resources and exercises function similarly.

There are some tables split across pages, which is distracting. Although many of the links, including re-directs work, several do not. Anyone using the text would need to update or replace - because this is a large number this would be a time-consuming task.

No problem with the writing, technically - at least not anything of a nature to raise this issue to a level of concern.

The heavy use of examples from published research provides a varied range of subject areas for readers, however not always in terms of cultural diversity specifically. While reading the text I was struck more by the diverse presentation than by a need for more inclusiveness. However, there was no offensive content. This part of the text's format however could be a way that users could augment the material by bringing in a more diverse array of examples.

Reviewed by Helen McManus, Adjunct Professor, Librarian, George Mason University on 6/20/17

This review considers this book's usefulness for a political science qualitative methods course. Political science programs typically require only quantitative methods training, therefore I am approaching this text with a distinct student... read more

The book is most comprehensive on questions of data gathering and research ethics. Blackstone quickly runs through research design and philosophy of social science questions. Chapters 6 and 7, on measurement and sampling, respectively, are useful reference points. Chapters 8 through 12 introduce approaches to gathering data--surveys, interviews, field research, content analysis, and, briefly, focus groups and experiments. These chapters explain the advantages and disadvantages of each approach, tips for using each approach, and a very brief note on analysis. Students would need additional readings, exercises, and exposure to software before analyzing any data they collect.

As a text covering both qualitative and quantitative methods, the book is a useful primer with a pragmatic approach to choice of methods (what does your question require?). Blackstone treats quantitative and qualitative methods in parallel, and convincingly construes them as complementary approaches. Chapters on sampling, interviews, and content analysis (under "unobtrusive methods"), for example, consider qualitative and quantitative methods in turn. Students with quantitative methods training may find this reassuring, as the book draws connections between the familiar and the unfamiliar.

Much of the book is applicable across the social sciences, though the discussion of levels of analysis, prominent theories, and library research tools are specific to sociology, as are example research questions. Instructors might supply, or ask students to come up with, examples suitable to political science. Sociology does not typically refer to "puzzles", so political science instructors would need to introduce that in other course materials.

There is no index or glossary.

Like other reviewers, I have some concerns about terminology, such as in the discussion of paradigms and theories in the earlier chapters.

I was struck that gender remains male/masculine, female/feminine, or "other, though. This is an outdated approach, both within and beyond the academy.

Blackstone uses some contemporary (ish) examples, such as the Brangelina phenomenon, but she explains them well enough to keep readers on board. Links out to videos and cartoons are an excellent idea, but some links are already dead (for example, in section 10.1 there is a dead link to a cartoon: Cotham, F. (2003, September 1). Two barbarians and a professor of barbarian studies. The New Yorker. Retrieved from http://www.cartoonbank.com/2003/two-barbarians-and-a-professor-of-barbarian-studies/invt/126562 )

This book is concise and easy to read. Blackstone uses clear, unpretentious language. In the online interface, readers can hover over bolded technical terms to see a quick definition.

I have no concerns here.

The chapters and sections lend themselves to easy rearrangement. For example, I plan to use chapter 15 (Research Methods in the Real World) belongs at the beginning of a course.

I am also incorporating sections of chapters into my online course. I find it helpful that each section of a chapter comes with its own learning objectives, key take aways, and exercises. Sections are clearly labeled, and the linked table of contents makes it easy to send students straight to a section of interest.

The chapters lead students from basic terminology to research design, on to data gathering, and then to possible uses of both research and newly acquired skills. I appreciate the early chapter on research ethics, prior to questions of research design.

Within each chapter, there are several sections of a manageable length. Each section opens with learning objectives, and closes with "key take aways" in a green box and "exercises" in a blue box.

The online interface is extremely simple. The most consistent navigation tool is a link to the Table of Contents, top and center of the interface. The additional navigation tools, though, vary somewhat. In some chapters, a reader can navigate to the next section (of that chapter); in other chapters, a similarly placed link allows the reader to navigate to the next chapter only. I found this inconsistency mildly troublesome, and quickly decided to rely on the ToC for moving between chapters and sections.

I notice that the PDF has unfortunately placed page breaks--some tables sit across two pages. The PDF also lacks a table of contents.

Blackstone writes in a casual tone, often using informal constructions and technically incorrect but ordinary usages. I find this inoffensive, and suspect that students will too. I noticed just one typographical error substantial enough to confuse a reader.

The text includes examples referring to gender roles, people of color, urban and rural contexts. As mentioned above, the use of male/female/other categories for gender is problematic, and hopefully would be addressed in any updates.

Citations are oddly inserted into sentences. Immediately following each regular in-text parenthetical citation, there is also a full (works cited list) citation, right there in the text. This is distracting.

Reviewed by Matthew DeCarlo, Assistant Professor, Radford University on 4/11/17

This book covers all of the important concepts in an introductory research methods text. Some of the more advanced concepts (e.g. types of validity and reliability) are cut out of this textbook, which is a choice I understand. Students are often overwhelmed by the more advanced concepts within a chapter. This book does a great job of focusing on the important parts of each concept.

The content inside the book is accurate. Definitions of key research concepts are explained correctly and clearly.

This book is relevant well outside of its own discipline of sociology. Additionally, the research used for examples is generally from the last few years. While those examples would need to be updated as time moves forward, the core content will remain relevant for decades.

The language used to write this research textbook is the best I have seen so far in my career as a research methods instructor. Students are often put off by research language, and the author does an excellent job of avoiding jargon and making her language plain.

The framework of the book is perhaps its greatest strength. The author has framed research concepts within the proper epistemological and ontological frameworks, which allows her even-handed treatment of qualitative and quantitative methods to cohere well within each section.

This is a highly modular book. Chapters are subdivided into smaller subsections, so they can be easily assigned and rearranged by professors teaching from the text. Because the pages are hosted in HTML format, students can follow links to each chapter and subsection, rather than scrolling through a long PDF.

Organization is remarkably clear throughout. Each chapter flows conceptually into the next.

I had problems with almost all of the graphics used in this textbook. They are referenced in the text and are often integral to understanding concepts as presented. This happened in both the HTML and PDF versions of the text. In spite of those issues, the overall ease of navigation was strong.

No grammar errors noted .

Culturally inclusive language is used throughout the text.

What is perhaps most promising about this text is that it is hosted on GitHub. Any professor who wanted to adapt this text for their discipline or make changes can easily do so using an HTML editor and GitHub.

Additionally, the author does a fantastic job of putting qualitative and quantitative research on equal footing, rather than relegating qualitative research to one or two chapters.

Reviewed by Mikaila Arthur, Associate Professor, Rhode Island College on 4/11/17

There is no index or glossary. The chapter on theory provides many useful explanations, but never focuses on the question of what theory or why it is an important part of sociological research. The chapter on research ethics is better. though in... read more

The chapter on theory provides many useful explanations, but never focuses on the question of what theory or why it is an important part of sociological research. The chapter on research ethics is better. though in discussing the issue of confidentiality it is important to mention that not all researchers promise confidentiality (see Mitch Duneier's "Sidewalk", for example) and that this is a controversial issue in research given the fact that some research participants would prefer their identities to be known. It would also be helpful to explain more about the IRB process and to talk about recent examples of research fraud and the replicability crisis.

The discussion of sociological questions uses language different from what most sociologists use, contrasting empirical questions to ethical--rather than normative--ones. Ethics, to me, are a subset of normative issues, not synonymous with them. However, the section on what makes a good question is very strong, though it never points out the importance of having a NEW question. In discussing the literature review process, the book focuses insufficient attention on the parts of the article important to reviewing literature--students following the author's advice are likely to turn in literature reviews focused on methods and limitations rather than findings.

The section on conceptualization is very good, and more thorough than in many texts. However, the discussion of operationalization is weaker, not giving students the foundation they need to really struggle through what many believe is the hardest part of the research methods curriculum. It would be useful to mention binary variables.

The discussion of sampling does not address appropriate sample size, margins of error, etc. The discussion of study design (cross-sectional, longitudinal, etc.) appears inside the survey research chapter, making it appear as if study design is not an important criterion in other sorts of research. But the discussion of survey question design is great.

The chapters on individual methods of data collection are generally stronger, though the chapter on unobtrusive measures would benefit from more attention to archival research. Also, the discussion of experiments would benefit from more attention both to the benefits of experiments for studying causality and the ethical issues that experiments raise. The chapter on sharing work should say more about the structure and format of articles and should contain a section on writing research proposals, as that is a key element of many research methods courses.

If this text were used in a one-semester research methods course, it probably has too little on data analysis; if it is used in the first semester of a two-semester course where analysis is covered separately, then the coverage of many topics seems a bit superficial.

In general, the content is accurate and unbiased, but there are a few exceptions. Many research methods instructors and textbooks would take issue with the way reliability and validity are defined here and the examples provided. The author also ought to present MUCH more in the way of cautions around convenience samples. The text also does not seem to understand the difference between a phone survey and an interview--but given the closed-ended (and machine-administered) nature of many contemporary phone surveys, there is a big difference. It also seems odd that focus groups are shunted off to a different chapter rather than treated as a kind of interview.

The discussion of measurement of gender, on page 71, seems to be a bit out-of-date--most scholars of gender now would suggest that just adding "other" to male and female is insufficient.

The most recent examples seem to come from about 2011, with more clustered between 2008 and 2010. While I absolutely agree that we should not have new editions just to have new editions, there does come a time when books begin to seem out of date. A couple of years from now, these examples will be from when our students were in middle school--so I hope there is a plan to update the book by then.

Examples, though, would generally seem relevant to students, and I like the examples from student work throughout the book (I do hope the author had permission to use them).

There are several instances in which the author uses terminology different from that typically used in research methods texts and courses. I wouldn't say the terminology is inaccurate, exactly, but it would require a major adjustment among instructors to adapt to using language consistent with the text. Otherwise, the writing is generally clear and terms are defined as needed.

There are some issues with internal consistency. For example, Table 2.1 on page 17 lays out four theoretical paradigms; table 2.2 on page 18 applies these paradigms to the sociology of sport, but it leaves one of them out with no explanation--these seem like editing problems more than authorial ones, though.

Many sections of the book are self-referential, which would make it hard to fully reorganize the text. This is especially notable in the section on reading research articles in chapter 15, which many instructors would want to use along with material from early in the text about the literature review process. Subsections are clearly marked with subheadings, but the format of the book would make it more difficult to locate, find, and separately assign these subsections.

Organization/Structure/Flow rating: 2

The text does seem to jump around quite a bit--the section on how to read research results occurs long after students are introduced to reading articles, for instance. In the chapters on different research methods, the discussion of strengths and weaknesses comes before students are fully introduced to those methods. And the lack of detailed table of contents or chapter summaries at the beginning of chapters makes it harder to follow the flow of the book.

Interface rating: 1

The text does not have a cover page or a table of contents.

The pagination is not very well done--tables break across pages in the middle of rows, for example. Similarly, headings sometimes occur at the end of pages, with the text on a subsequent page. Fonts sometimes seem to change sizes, particularly for endnote references and and table titles referred to in the text (and endnote numbers are not clickable, which seems unfortunate in an electronic text). A number of links referred to in the text are broken. It would be helpful to have a detailed table of contents laying out chapter subsections. Some keywords appear in bold and others do not. There are editing errors, typos, spaces missing after periods, etc. Many figures are indicated but are missing (for example, diagrams of inductive and deductive research processes are mentioned, but they do not appear in the text--this is a really bad omission). Generally, this text does not make use of any of the features which would be beneficial in an online text, but yet is not set up to be a well-designed print text.

Other than typos, as referenced in the interface section, I noted no issue with grammar or writing.

I did not notice anything which was culturally insensitive of offensive. Examples were generally appropriate, though primarily focused on American sociology. Given the author's scholarly focus as a sociologist of gender, work, and family, it should not be suprising that examples are more likely to relate to these areas, leaving issues of race, sexuality, ethnicity, immigration, language, religion, disability, etc. to have much lesser coverage. Given that this is a research methods course, this may not be a primary concern for many instructors, but those teaching in very diverse institutions may want to think about whether the text has sufficient relevance to their students' backgrounds, concerns, and experiences. I would also point out here that the text does seem to assume a traditionally-aged residential classroom composition, not the norm for many of us.

The text includes suggested exercises, but these are not really exercises. Some are discussion questions, others suggest students "check out" links or view images which are not contained within the text (no link given). I do not recommend instructors use this text unless they really have no other adequate alternatives--the lack of appropriate visuals, editing errors, etc. make it easy for students accustomed to higher-quality resources to dismiss it, and you'd be just as well off using a collection of websites as this.

Reviewed by Alexa Smith-Osborne, Professor, University of Texas at Arlington on 4/11/17

This text's comprehensiveness, in combination with simple language suited to first exposure to the topic, is one of the chief strengths of the book. However, community-based participatory action research methods were not included in this text, thus reducing its utility for the social work discipline. I especially liked the linked in-text definitions, which provide an easy-to-use glossary to enhance reading comprehension for undergraduates.

The text is accurate and unbiased for its discipline. For optimal utility in social work teaching, the text would need to be used with a companion file using social work examples, including social justice-focused research using community-based participatory action methods. These methods were not included in this text.

Relevance/longevity of content is one of the main objectives of this textbook. For social work, chapters 14 “Reading and Understanding Social Research” and 15 “Research Methods in the Real World”, are the most directly relevant since, as a profession, we do applied research.

Its simple language makes it accessible to most undergraduates, and the in-text "drop-down" definitions provide adequate support to allow comprehension of technical terminology.

The content was internally consistent, and sufficient aids were provided in tables and headings/subheadings to promote consistency.

Tie-ins to earlier material, tables, and headings/subheadings made the text easily divisible into smaller reading sections and discrete modules for instructor use.

Accessibility is one off the main objectives of this text. It succeeded in reaching this objective, through logical and clear organization, structure, and flow, including many connectors to earlier concepts.

The online version had greater interface than the pdf version, but both were useable.

I did not see any grammatical errors.

Cultural diversity is discussed within the context of the social constructivist theoretical perspective. Measurement and study examples which focus on cultural differences are presented throughout, making this text particularly syntonic with social work values. The text makes use of examples that are inclusive of a variety of races, ethnicities, and backgrounds.

With a companion portfolio of materials on community-based participatory action methods and social justice-focused research examples, this text would be suitable to use in an undergraduate social work research course.

Reviewed by Robert Liebman, Professor, Portland State University on 2/8/17

Text is comprehensive in two senses: it covers what is standard in Research Methods texts and it serves the author’s focus on teaching research design/methods to prepare students for undertaking a research project (or doing a research proposal). Late in the book (159) is review of 6 key “diagnostic” questions on a research project: Why? How? For whom? What conclusions can I draw? Knowing what I know now, what would I do differently? How could the research be improved? These are diagnostic questions, to ask at the end of a project (and could be used as guidelines that reflect a grading rubric). Missing for me at the start are: a) flow-chart that would list of the steps in doing a project, roughly: 1. Turning an interest into a research question, 2. Design the research, 3. Choosing appropriate methods, 4. Collecting Data, 5. Summarizing/Synthesizing, 6. Write up a report & b) a look-forward to the last chapters including the 6 key “diagnostic” questions that says what you will learn from the book I like that the text conveys to students a sense of agency – if you learn methods, you can design/do research. I like section 13.3 which suggests that sociologists write for both academic or public audiences. The author comes to the writing having done both academic and public sociology – that adds a engaging perspective lacking from mainstream texts (Babbie, Schutt) Great ! On that point, a special feature of the text is the final chapter (Research Methods in the Real World) that gives a rationale for the benefits/payoffs of studying sociology: getting a job/building a career, being a judge of research reported in the media. One regret is that too little is said of the payoff having sociological research skills (surveys, statistical training) for doing environmental stewardship and public citizenship I used the pdf and think most students will not be logged on while reading the text. It does not provide a Table of Contents, glossary, or an index. Adding them would make much easier to use the book. BTW Table 15.1 "Transferable Skills Featured in This Text" could be redone as a TofContents.

There are many strong chapters (measurement, survey methods, fieldwork plus other qualitative methods that are sometimes left out) and well-written sections (conceptualization, operationalization) But I found Ch 2 Linking Theory with Methods confusing. The setup says it will cover “connections between paradigms, social theories, and social scientific research methods. We’ll also consider how one’s analytic, paradigmatic, and theoretical perspective might shape or be shaped by her or his methodological choices” Then: “While paradigms may point us in a particular direction with respect to our “why” questions, theories more specifically map out the explanation, or the “how,” behind the “why.” We go from 4 paradigms to 3 theoretical perspectives in a chart of examples on sport – these are illustrated but not well-explained. I like the treatment of styles of doing research in Charles Ragin, Constructing Social Research

I found discussion of micro-, meso-, and macro confusing. One study question asks: “Identify and distinguish between micro-, meso-, and macrolevel considerations with respect to the ethical conduct of social scientific research” Hard to answer based on text

I think that the terms “nomothetic” and “ideographic” are not well-defined nor is the link btw causality and tests of hypotheses well-explained. The matter of “falsifiability” is not discussed In my view, most confusing chapter.

Text lacks a discussion of control in the section on experimental design Might ask students what prior knowledge of experiments they got before coming into the course

I believe there is confusion about the roles of quantitative/qualitative in confirmation vs contextualization (p56) Multi-methods folks sometimes use “theoretical” sampling to assemble focus groups to clarify (more than contextualize) survey responses from subgroups

One small error: Rik Scarce studied radical environmental movement, not animal rights

Up-to-date and easily updated

Here the book shines. Major strengths: clear writing, engaging research examples, easy-to-understand tables, plus provides Learning objectives/Takeaways that encourage preview and review by students Re use of jargon/technical terminology – Add glossary

Internally consistent – enhanced by “look-back” devices such as Table 15.1 "Transferable Skills Featured in This Text"

High modularity both of chapters: Easy to re-arrange the order to fit different instructor’s styles and of entries: Short and crisp – can be read in a short sitting. As written, allows instructors to insert other examples/illustrations or remove sections that are less central (eg Conversation Analysis)

The inclusion of links to YouTube and other media (Colbert interview with Sudhir Venketash) is a very important feature that allows instructors to have students preview at home & review in class for discussion .... The book opens way to using resources outside of it

I might introduce What is Sociology? ahead of Ethics – but that option is open to an adopter of the book

Online and pdf versions differ – While most links work in pdf, it does not include some Figures, Table of Contents

No objections to author’s usage. Some sentences are truncated. (p55)

In my view, not culturally insensitive or offensive. However, the book has a bias in that it reflects Armstrong’s research on women’s movements & sexual harassment. Few examples address race, ethnicity, class – These could be added for balance and reaching instructors who cover fields different from author.

I love how the book invites students to engage the topic by sharing examples of the topics offered by students in her course.

A strong text that matches the organization of standard texts which replicate themselves from generation to generation. Hoping to go beyond them, I wish the text had more full-blown discussions of how sociologists write for different audiences as in Charles Ragin, Constructing Social Research and of how sociologists make inferences from data (which comes into some of the examples eg The Second Shift). Give a bit more on how to write up results

Reviewed by Anna Berardi, Professor, George Fox University on 2/8/17

This text is comprehensive in scope and depth of content. The HTML version is extremely effective in helping the reader identify material as listed in the ToC. The PDF and DOCx versions are difficult to manage and do not have an attached ToC. read more

This text was written by a professor who teaches this material in the higher ed setting. His expertise and familiarity with how to make this subject matter accessible is evident.

This text is covering both timeless, mainstream research methods relevant to all social and behavioral science professions, as well as newer methods common in post-modern research.

The layout makes the information very easy to access. The outline / section formatting "chunks" (breaks down into manageable form) information that is otherwise dry when assembled in the traditional narrative format.

Concepts build on each other, and consistent language is used throughout.

As I was reviewing clarity, its strength is its use of divided sections - very nicely done making the text easy to use.

Research methods has a natural flow to the way information builds on each other, and that is evident in this text.

Loved manuevering in HTML, but had preferred PDF so I could annotate. Wished that the ToC was in all formats.

Well edited; no issues with grammatical errors.

Sociology is by nature aware of contextual identities, and this is evident in the types of examples given.

Two main recommendations: 1. Please make the author's name visible 2. Please include the Table of Contents attached to all versions of the text.

Thank you for a great resource!

Reviewed by Noelle Chesley, Associate Professor, University of Wisconsin-Milwaukee on 1/7/16

I find the text to be very comprehensive. I think it covers most of the topics and subtopics one would expect to see in an undergraduate sociology research methods text. However, within topics, this text may not cover details as comprehensively as some other texts out there (I describe the texts I am familiar with at the end of this review). Just as one example, in the survey research chapter (ch. 8), the author(s) point out that different methods of survey delivery (in person, online, etc.) have pros and cons, but these are not contrasted in any detail, particularly in terms of how they might influence response rates or allow (or not) for sufficient coverage of the sampling frame. However, for those instructors that incorporate a research project (such as developing a research proposal), the text covers elements of research planning, design, and development that are not necessarily well-covered in some other texts, an addition which I believe adds to the texts’ comprehensiveness. The final chapter (Research methods in the Real World) that connects research skills to possible career tracks and one’s role as an engaged citizen is excellent and is material that is often not present in these sorts of books, but should be.

My read suggests that this text is generally accurate. I was not aware of any instances of bias in the presentation of material (although as a white, women academic, I may be subject to the same biases as the author of the book!).

In thinking about the relevance/longevity of a research methods text, I would focus on: 1) examples used to illustrate key concepts; and 2) how up-to-date more rapidly changing topics are in terms of addressing areas of development (survey methods, sampling). This text utilizes examples (like illustrations from President Obama’s election), that may seem dated at some point. On the other hand, the topic on survey research accurately (see point 2, above) reflects the current state of knowledge about the relationship between survey response rates and the potential for bias. This is an area that has been changing rapidly, so keeping up with current state of knowledge will be important. In general, though the examples and cultural references are those most likely to date a text. There are such references in this text that may make students say “huh?” in just a few years.

Clarity rating: 3

In general, writing clarity is a strength of this text. Overall, the ideas are delivered in a very clear, understandable way. However, one element that detracted from clarity for me were embedded, full citations in the text. Throughout the book, when a particular research study is mentioned, the entire citation is embedded in the sentence, which was cumbersome to encounter as a reader. In addition, there are places where the clarity of the text falls apart (see point 10 in this rating for more). The embedded citations are cumbersome enough, that I think they detract substantially from clarity, which is reflected in my rating.

I found the text to be generally consistent in terms of use of terminology and framework.

There is an inherent tradeoff in writing a text that utilizes hyperlinks and makes references to earlier sections or discussions and modularity, or the ability to use portions of the text in a stand-alone fashion. I do think it would be possible to use sections of the text, rather than the whole text, to support teaching in particular areas. There will be some references to material in previous chapters or sections that the student has not read, but many of the chapters could also stand on their own to support teaching of a particular topic in research methods.

The organization of ideas and subtopics adds to the overall clarity. Similar ideas are grouped together and hyperlinks back to earlier ideas in later sections reinforce the organization, which enhances the overall clarity of the text (see clarity, above).

The .pdf of the text does not contain a table of contents, which I found limiting in using the text. There is also no information about the author in the beginning of the document. The only way to get either of these pieces of information is in the open text web entry for this book. The text does contain a number of hyperlinks. While I did not try every link (not even close), my own attempt to use some of these found just a few that don’t work (e.g., the link at the bottom of p. 9). Most links, however, did connect as expected. There are also places within the text where the font changes—this is distracting.

There are regular writing errors in the text. For instance, in section 9.1, it looks like a sentence referencing Regis Filban (will anyone know who this is in a few years?) was cut off and lives as a fragment in the current version. In fact, this whole opening paragraph is not well-written. Similar problems are apparent in the opening paragraph of chapter 10.

In thinking about cultural relevance in a research methods text, I tried to think about the descriptions of research—what sorts of examples get used to illustrate particular techniques or problems, as well as depictions of what a methods student might look like. In terms of research examples, I think the text utilizes a fairly wide variety of examples, although studies focused on gender seemed more common than those investigating race/ethnicity or class, for example. I also noted one instance of depictions of methods students (p. 152, focus group chapter) that provided illustrations of research participants using names like “Sally,” “Joe” and “Ashley.” A more diverse set of names (Jose, Darnisha, etc.) in an instance like this might add to cultural relevance of the text.

? I have been regularly teaching undergraduate research methods since 2005, and I teach in both in-person and fully online formats. I have been using Schutt’s Investigating the Social World as my primary teaching text in these courses, and this is the book that was my implicit comparison as I read the Blackstone text. However, I am also familiar with Neuman’s text and had parts of that book in mind, as well, as I read this text. The strengths of the text include its coverage of how to construct research questions and research documents as well as how the skills developed in an undergraduate course might translate to life outside of higher education. Weaknesses include a still “rough” look to the final document and some topic areas where coverage might not be as detailed as one would like. Overall, a solid text that has the potential to make teaching research methods more affordable for students.

Reviewed by Alison Bianchi, Associate Professor, University of Iowa on 1/7/16

This textbook covers all of the research methods needed for an undergraduate level research methods course. I have specific concerns that I will address in the "accuracy" section, but overall I am pleased with this book. I have used it in one... read more

However, as far as I could tell (and just in case I missed an update, I just downloaded the PDF from Saylor's Website just now), there is no glossary or index for this book. It would be great to have at least a glossary of terms, as there are quite a few! Given that this is one of the criteria for comprehensiveness, I do have to grade accordingly.

The author works very hard to diminish biases that are often found in Research Methods texts, and are taught in classes. Dr. Blackstone is no "Methods snob" -- she does the correct thing by telling students that it is the nature of research question that should drive one to use the method. This means that no method should be privileged just because the researcher(s) prefers it.

As far as accurate and error free, this is where I have concerns. I'll address them one by one:

(1) When discussing the micro-meso-macro level definitions and examples on page 13, the author muddles the concepts by suggesting that the meso-level is about studying groups, and the micro-level is more about individuals. Actually, micro-level scholars study groups, too. Accordingly, the author should use some definitions from the sociology of organizations literature, and define the meso-level as that which describes ORGANIZATIONS and the micro-level as potentially for SMALL GROUPS, such as dyads and triads. This issue is also found on page 14, first two full paragraphs.

(2) In the "Sociological Theories" section starting on page 17, the author has some problems discussing what is and isn't theory. The problem, of course, is not the author's, but rather the fact that sociologists cannot agree on what is theory! Accordingly, there's a way to deal with this issue -- I recommend using Abend's (2008) typology for the 7 ways that sociologists discuss theory. For example, some would say that "symbolic interactionism" is NOT a theory, but rather a paradigm. So, the discussion of what a theory is and what a paradigm is gets muddled and confusing for students. Using the aforementioned typology will help sort this out.

(3) In the section on IRB, page 25, the authors states that there are "human" and "non-human" sources of information, and that the "human" one refers to human subjects and the "non-human" one refers to data derived from humans, such as content analyses. However, there is a third possibility, and that is that "non-human" subjects are animals that are not homo sapiens. The IRB protocols for these subjects is a whole different ball of wax!! So, I would just use the terms "human" and "non-living" throughout.

(4) On page 52, the terms "idiographic" and "nomothetic" are poorly defined, as well as throughout the text, and not well linked to the concepts of qualitative and quantitative research throughout the text, or to the concepts of deductive or inductive ways of knowing. I recommend a brief history of the concepts and a better way to connect all of these notions of the theory-data linkage.

(5) In the section on causality, around page 54, I had many red flags. First, you simply cannot say that any qualitative method reveals causal relationships. This method is not designed for that! Qualitative research can suggest hypotheses, but it cannot reveal relationships. And, quite frankly, for other reasons, neither can quantitative methods! The author really must discuss the difference between causal theory and hypothesized relationships -- any test of a hypothesis can never be a perfect test of causation. Nomothetic theory can conceptualize it, but quantitative tests can never, ever completely capture causation.

(6) When discussing hypotheses on page 59, hypotheses have two other qualities that are of utmost importance: (1) falsifiability and (2) repeatability.

(7) On page 61, the use of the term "triangulation" is interesting. I realize that in the feminist literature that this is a way to describe multi-method studies, but it's confusing for students because triangulation is also a technique for qualitative studies to collect many points of view. I realize that this is problem with so many concepts in research methods -- take the term "control", for example. We have control variables, control conditions, experimental control -- just too many concepts that are different, but use the same word. Can we avoid this for yet another concept?

(8) The section on Experiments is not great. First, "true experiments" are not ones with experiment and control conditions -- they are those that use random assignment. "Quasi-experiments", including those with just post-tests, are those without this technique. And yes, experimentalists have to deal with external validity, but the author writes the text as if they have never considered that or found ways to deal with it. That's simply not true. In general, I just don't use this section when I teach experiments.

(9) I found the chapters on measurement and operationalization, survey methods, and qualitative methods to be first rate!

The content is up-to-date, and can be easily updated. However, I would like to see more examples of data collection using the Internet, social media, and other digital media.

I found the prose to be very accessible, and so did my students. The author does have a much more casual tone than other Research Methods books (for example, she uses "OK" a lot), but I like that, and so do my students. Methods is dry enough -- why not make the text more accessible and readable?

The text is very internally consistent. Dr. Blackstone correctly refers back to examples and concepts throughout the book.

I do think that the modularity is well done. In fact, I could easily assign chapters out of order. For instance, I always start my methods courses with ethics before we do anything else. That chapter stands alone very well, and can be assigned right away. Also, the chapter referring to "what is sociology" is somewhere around Chapter 4, but I just assign that next.

I would change the order of the topics, but this is just my style. Most Research Methods books follow the format of the author's, so that OK. However, Chapter 2's content on theory meanders a bit. I would reorganize it to start with paradigms, then theories, then the micro-meso-macro discussion.

We need a Table of Contents!!! And, throughout the text there are references to figures ... I looked in the back of the book, I downloaded it a couple of times to see if my computer was the problem, etc. No -- there are no figures!

I caught many mistakes. While Dr. Blackstone likes to split infinitives and use "in order to", a phrase that should be struck from the English language, I'm willing to forgive! However, there were typos that were problematic -- I'm not going to list all of them, but see page 55, paragraphs 5 and 6, for example. Both paragraphs have sentences that end with "in ." Weird.

I would do another thorough edit.

Dr. Blackstone goes out of her way to make sure that she is inclusive, especially with her research examples.

I really liked how Dr. Blackstone discusses what it's like to be a professional sociologist. Many of my students wonder: (1) what do I do and (2) what kind of jobs that they can get with a degree in Sociology? It's nice that Dr. Blackstone includes examples from her own life, and explains to the students that being a strong methodologist could one day land them a job!

Reviewed by Susan Burke, Associate Professor, University of Oklahoma on 1/12/15

I used two online textbooks for my Fall 2014 course and this Blackstone text was far more comprehensive than the other one. It contained either chapters or short sections on nearly everything that I wanted to cover with the course, although for... read more

To the best of my knowledge the text was accurate. One student commented in the course evaluation that he found several typos in the text and that undermined his faith in the content, so possibly the book could use a check up by a copy editor.

This is a research methods book written specifically for undergraduate sociology students and it does a very good job of molding the information to fit that audience. I happened to be using the text for an introductory master's course in a different subject field, so the very purposeful focus on sociology made the book somewhat less translatable. In order to help my students make the cognitive leap to apply the concepts to their interests, I supplemented the text with articles and other readings from my discipline.

The book is well-written in a manner that makes the concepts clear and easy to understand for students who are beginners to research methods.

The book's structure and style was consistent across chapters and sections.

This book was available in two versions, a web version where you would click on a chapter from the index and it would take you to a separate page for that chapter, and a full length PDF. I strongly preferred the clickable web version as it was easier to jump right to the needed section, and I would use that to give the specific web site address for the chapter to students weekly. Many chapters were further divided into sections which were also linked so one could jump directly to that section of the chapter. This was a very useful feature.

The book was not arranged in the order in which I present the topcis in the course that I teach. However, the order that the author used is logical.

This was excellent. It was easy to access and easy to navigate. Several students reported being delighted with their ability to access and use the text easily from anywhere that was internet-enabled. One student suggested that the interface could be enhanced with a navigation bar on the side of the page that would facilitate jumping to other chapters.

I have no opinion on this - while I didn't notice grammatical errors, it's possible that they may exist in the text.

The author has given examples from sociological studies that have examined controversial topics, but she has done so with care and in a non-offensive manner.

There are some features of published works that were not available with this textbook. One is a date. I was unable to find any indication of when the book was written. Another is that it has no index. That is one function for which the PDF was a better option as one can use the "find" feature for keywords throughout the text.

Chapter 1: Introduction
Chapter 2: Linking Methods With Theory
Chapter 3: Research Ethics
Chapter 4: Beginning a Research Project
Chapter 5: Research Design
Chapter 6: Defining and Measuring Concepts
Chapter 7: Sampling
Chapter 8: Survey Research: A Quantitative Technique
Chapter 9: Interviews: Qualitative and Quantitative Approaches
Chapter 10: Field Research: A Qualitative Technique
Chapter 11: Unobtrusive Research: Qualitative and Quantitative Approaches
Chapter 12: Other Methods of Data Collection and Analysis
Chapter 13: Sharing Your Work
Chapter 14: Reading and Understanding Social Research
Chapter 15: Research Methods in the Real World

Ancillary Material

About the book.

The author of Principles of Sociological Inquiry: Qualitative and Quantitative Methods , Amy Blackstone, started envisioning this textbook while sitting in her own undergraduate sociology research methods class. She enjoyed the material but wondered about its relevance to her everyday life and future plans (the idea that one day she would be teaching such a class hadn't yet occurred to her).

Now that she teaches the research methods course, she realizes that students today wonder the very same thing. While the importance of understanding research methods is usually clear to those students who intend to pursue an advanced degree, Amy wanted to write a text that would assist research methods teachers in demonstrating to all types of students the relevance of this course.

In addition, Amy Blackstone's experience as an active researcher who uses both qualitative and quantitative methods made her acutely aware of the need for a balanced approach in teaching methods of sociological inquiry.

Together, Amy Blackstone's experiences as a student, researcher, and teacher shape the three overriding objectives of Principles of Sociological Inquiry: Qualitative and Quantitative Methods: Relevance, Balance, and Accessibility.

Principles of Sociological Inquiry: Qualitative and Quantitative Methods emphasizes the relevance of research methods for the everyday lives of its readers, undergraduate students.Each chapter describes how research methodology is useful for students in the multiple roles they fill:

As consumers of popular and public information
As citizens
As current and future employees. Connections to these roles are made throughout and directly within the main text of the book

Principles of Sociological Inquiry: Qualitative and Quantitative Methods also provides balanced coverage of qualitative and quantitative approaches by integrating a variety of examples from recent and classic sociological research. The text challenges students to debate and discuss the strengths and weaknesses of both approaches.

Finally, one of the most important goals Amy had for Principles of Sociological Inquiry: Qualitative and Quantitative Methods was to introduce students to the core principles of social research in a way that is straightforward and engaging. As such, the text reflects public sociology's emphasis on making sociology accessible and readable. No one can validate that claim more than a teacher or student. So, take a look for yourself today and review Principles of Sociological Inquiry: Qualitative and Quantitative Methods by Amy Blackstone to see if its approach toward relevance, balance, and accessibility are right for your course and students.

About the Contributors

Amy Blackstone is Associate Professor and Chair of Sociology at the University of Maine. Using qualitative and quantitative methods, her research includes studies of workplace harassment, childfree adults, and activism in the breast cancer and anti-rape movements. Her work has appeared in a variety of journals and edited volumes including Gender & Society, Law & Society Review, American Sociological Review, and Journal of Contemporary Ethnography. Blackstone has served as a Consulting Editor for Contexts, the American Sociological Association’s public-interest magazine. She is currently a member of the Social Science Research Group on the University of Maine’s National Science Foundation ADVANCE grant, for which she examines faculty satisfaction and the recruitment, retention, and advancement of women faculty in particular. Blackstone enjoys her work with numerous undergraduate research assistants and student clubs. In 2011 she received the University of Maine’s College of Liberal Arts and Sciences Outstanding Faculty Award in Teaching/Advising. Blackstone received her Ph.D. in Sociology at the University of Minnesota and her B.A. in Sociology at Luther College.

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Soc 156: Quantitative Methods in Sociology

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2.2 Research Methods

Learning objectives.

By the end of this section, you should be able to:

Recall the 6 Steps of the Scientific Method
Differentiate between four kinds of research methods: surveys, field research, experiments, and secondary data analysis.
Explain the appropriateness of specific research approaches for specific topics.

Sociologists examine the social world, see a problem or interesting pattern, and set out to study it. They use research methods to design a study. Planning the research design is a key step in any sociological study. Sociologists generally choose from widely used methods of social investigation: primary source data collection such as survey, participant observation, ethnography, case study, unobtrusive observations, experiment, and secondary data analysis , or use of existing sources. Every research method comes with plusses and minuses, and the topic of study strongly influences which method or methods are put to use. When you are conducting research think about the best way to gather or obtain knowledge about your topic, think of yourself as an architect. An architect needs a blueprint to build a house, as a sociologist your blueprint is your research design including your data collection method.

When entering a particular social environment, a researcher must be careful. There are times to remain anonymous and times to be overt. There are times to conduct interviews and times to simply observe. Some participants need to be thoroughly informed; others should not know they are being observed. A researcher wouldn’t stroll into a crime-ridden neighborhood at midnight, calling out, “Any gang members around?”

Making sociologists’ presence invisible is not always realistic for other reasons. That option is not available to a researcher studying prison behaviors, early education, or the Ku Klux Klan. Researchers can’t just stroll into prisons, kindergarten classrooms, or Klan meetings and unobtrusively observe behaviors or attract attention. In situations like these, other methods are needed. Researchers choose methods that best suit their study topics, protect research participants or subjects, and that fit with their overall approaches to research.

As a research method, a survey collects data from subjects who respond to a series of questions about behaviors and opinions, often in the form of a questionnaire or an interview. The survey is one of the most widely used scientific research methods. The standard survey format allows individuals a level of anonymity in which they can express personal ideas.

At some point, most people in the United States respond to some type of survey. The 2020 U.S. Census is an excellent example of a large-scale survey intended to gather sociological data. Since 1790, United States has conducted a survey consisting of six questions to received demographical data pertaining to residents. The questions pertain to the demographics of the residents who live in the United States. Currently, the Census is received by residents in the United Stated and five territories and consists of 12 questions.

Not all surveys are considered sociological research, however, and many surveys people commonly encounter focus on identifying marketing needs and strategies rather than testing a hypothesis or contributing to social science knowledge. Questions such as, “How many hot dogs do you eat in a month?” or “Were the staff helpful?” are not usually designed as scientific research. The Nielsen Ratings determine the popularity of television programming through scientific market research. However, polls conducted by television programs such as American Idol or So You Think You Can Dance cannot be generalized, because they are administered to an unrepresentative population, a specific show’s audience. You might receive polls through your cell phones or emails, from grocery stores, restaurants, and retail stores. They often provide you incentives for completing the survey.

Sociologists conduct surveys under controlled conditions for specific purposes. Surveys gather different types of information from people. While surveys are not great at capturing the ways people really behave in social situations, they are a great method for discovering how people feel, think, and act—or at least how they say they feel, think, and act. Surveys can track preferences for presidential candidates or reported individual behaviors (such as sleeping, driving, or texting habits) or information such as employment status, income, and education levels.

A survey targets a specific population , people who are the focus of a study, such as college athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes. Most researchers choose to survey a small sector of the population, or a sample , a manageable number of subjects who represent a larger population. The success of a study depends on how well a population is represented by the sample. In a random sample , every person in a population has the same chance of being chosen for the study. As a result, a Gallup Poll, if conducted as a nationwide random sampling, should be able to provide an accurate estimate of public opinion whether it contacts 2,000 or 10,000 people.

After selecting subjects, the researcher develops a specific plan to ask questions and record responses. It is important to inform subjects of the nature and purpose of the survey up front. If they agree to participate, researchers thank subjects and offer them a chance to see the results of the study if they are interested. The researcher presents the subjects with an instrument, which is a means of gathering the information.

A common instrument is a questionnaire. Subjects often answer a series of closed-ended questions . The researcher might ask yes-or-no or multiple-choice questions, allowing subjects to choose possible responses to each question. This kind of questionnaire collects quantitative data —data in numerical form that can be counted and statistically analyzed. Just count up the number of “yes” and “no” responses or correct answers, and chart them into percentages.

Questionnaires can also ask more complex questions with more complex answers—beyond “yes,” “no,” or checkbox options. These types of inquiries use open-ended questions that require short essay responses. Participants willing to take the time to write those answers might convey personal religious beliefs, political views, goals, or morals. The answers are subjective and vary from person to person. How do you plan to use your college education?

Some topics that investigate internal thought processes are impossible to observe directly and are difficult to discuss honestly in a public forum. People are more likely to share honest answers if they can respond to questions anonymously. This type of personal explanation is qualitative data —conveyed through words. Qualitative information is harder to organize and tabulate. The researcher will end up with a wide range of responses, some of which may be surprising. The benefit of written opinions, though, is the wealth of in-depth material that they provide.

An interview is a one-on-one conversation between the researcher and the subject, and it is a way of conducting surveys on a topic. However, participants are free to respond as they wish, without being limited by predetermined choices. In the back-and-forth conversation of an interview, a researcher can ask for clarification, spend more time on a subtopic, or ask additional questions. In an interview, a subject will ideally feel free to open up and answer questions that are often complex. There are no right or wrong answers. The subject might not even know how to answer the questions honestly.

Questions such as “How does society’s view of alcohol consumption influence your decision whether or not to take your first sip of alcohol?” or “Did you feel that the divorce of your parents would put a social stigma on your family?” involve so many factors that the answers are difficult to categorize. A researcher needs to avoid steering or prompting the subject to respond in a specific way; otherwise, the results will prove to be unreliable. The researcher will also benefit from gaining a subject’s trust, from empathizing or commiserating with a subject, and from listening without judgment.

Surveys often collect both quantitative and qualitative data. For example, a researcher interviewing people who are incarcerated might receive quantitative data, such as demographics – race, age, sex, that can be analyzed statistically. For example, the researcher might discover that 20 percent of incarcerated people are above the age of 50. The researcher might also collect qualitative data, such as why people take advantage of educational opportunities during their sentence and other explanatory information.

The survey can be carried out online, over the phone, by mail, or face-to-face. When researchers collect data outside a laboratory, library, or workplace setting, they are conducting field research, which is our next topic.

Field Research

The work of sociology rarely happens in limited, confined spaces. Rather, sociologists go out into the world. They meet subjects where they live, work, and play. Field research refers to gathering primary data from a natural environment. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In field work, the sociologists, rather than the subjects, are the ones out of their element.

The researcher interacts with or observes people and gathers data along the way. The key point in field research is that it takes place in the subject’s natural environment, whether it’s a coffee shop or tribal village, a homeless shelter or the DMV, a hospital, airport, mall, or beach resort.

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviors in that setting. Field work is optimal for observing how people think and behave. It seeks to understand why they behave that way. However, researchers may struggle to narrow down cause and effect when there are so many variables floating around in a natural environment. And while field research looks for correlation, its small sample size does not allow for establishing a causal relationship between two variables. Indeed, much of the data gathered in sociology do not identify a cause and effect but a correlation .

Sociology in the Real World

Beyoncé and lady gaga as sociological subjects.

Sociologists have studied Lady Gaga and Beyoncé and their impact on music, movies, social media, fan participation, and social equality. In their studies, researchers have used several research methods including secondary analysis, participant observation, and surveys from concert participants.

In their study, Click, Lee & Holiday (2013) interviewed 45 Lady Gaga fans who utilized social media to communicate with the artist. These fans viewed Lady Gaga as a mirror of themselves and a source of inspiration. Like her, they embrace not being a part of mainstream culture. Many of Lady Gaga’s fans are members of the LGBTQ community. They see the “song “Born This Way” as a rallying cry and answer her calls for “Paws Up” with a physical expression of solidarity—outstretched arms and ﬁngers bent and curled to resemble monster claws.”

Sascha Buchanan (2019) made use of participant observation to study the relationship between two fan groups, that of Beyoncé and that of Rihanna. She observed award shows sponsored by iHeartRadio, MTV EMA, and BET that pit one group against another as they competed for Best Fan Army, Biggest Fans, and FANdemonium. Buchanan argues that the media thus sustains a myth of rivalry between the two most commercially successful Black women vocal artists.

Participant Observation

In 2000, a comic writer named Rodney Rothman wanted an insider’s view of white-collar work. He slipped into the sterile, high-rise offices of a New York “dot com” agency. Every day for two weeks, he pretended to work there. His main purpose was simply to see whether anyone would notice him or challenge his presence. No one did. The receptionist greeted him. The employees smiled and said good morning. Rothman was accepted as part of the team. He even went so far as to claim a desk, inform the receptionist of his whereabouts, and attend a meeting. He published an article about his experience in The New Yorker called “My Fake Job” (2000). Later, he was discredited for allegedly fabricating some details of the story and The New Yorker issued an apology. However, Rothman’s entertaining article still offered fascinating descriptions of the inside workings of a “dot com” company and exemplified the lengths to which a writer, or a sociologist, will go to uncover material.

Rothman had conducted a form of study called participant observation , in which researchers join people and participate in a group’s routine activities for the purpose of observing them within that context. This method lets researchers experience a specific aspect of social life. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behavior. A researcher might work as a waitress in a diner, experience homelessness for several weeks, or ride along with police officers as they patrol their regular beat. Often, these researchers try to blend in seamlessly with the population they study, and they may not disclose their true identity or purpose if they feel it would compromise the results of their research.

At the beginning of a field study, researchers might have a question: “What really goes on in the kitchen of the most popular diner on campus?” or “What is it like to be homeless?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside.

Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in analyzing data and generating results.

In a study of small towns in the United States conducted by sociological researchers John S. Lynd and Helen Merrell Lynd, the team altered their purpose as they gathered data. They initially planned to focus their study on the role of religion in U.S. towns. As they gathered observations, they realized that the effect of industrialization and urbanization was the more relevant topic of this social group. The Lynds did not change their methods, but they revised the purpose of their study.

This shaped the structure of Middletown: A Study in Modern American Culture , their published results (Lynd & Lynd, 1929).

The Lynds were upfront about their mission. The townspeople of Muncie, Indiana, knew why the researchers were in their midst. But some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviors of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behavior. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job.

Once inside a group, some researchers spend months or even years pretending to be one of the people they are observing. However, as observers, they cannot get too involved. They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the end results are often descriptive or interpretive. The researcher might present findings in an article or book and describe what he or she witnessed and experienced.

This type of research is what journalist Barbara Ehrenreich conducted for her book Nickel and Dimed . One day over lunch with her editor, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered. Someone should do a study . To her surprise, her editor responded, Why don’t you do it?

That’s how Ehrenreich found herself joining the ranks of the working class. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter.

She discovered the obvious, that it’s almost impossible to get by on minimum wage work. She also experienced and observed attitudes many middle and upper-class people never think about. She witnessed firsthand the treatment of working class employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

The book she wrote upon her return to her real life as a well-paid writer, has been widely read and used in many college classrooms.

Ethnography

Ethnography is the immersion of the researcher in the natural setting of an entire social community to observe and experience their everyday life and culture. The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a social group.

An ethnographic study might observe, for example, a small U.S. fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or an amusement park. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a determined amount of time studying every aspect of the chosen place, taking in as much as possible.

A sociologist studying a tribe in the Amazon might watch the way villagers go about their daily lives and then write a paper about it. To observe a spiritual retreat center, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record data, and collate the material into results.

Institutional Ethnography

Institutional ethnography is an extension of basic ethnographic research principles that focuses intentionally on everyday concrete social relationships. Developed by Canadian sociologist Dorothy E. Smith (1990), institutional ethnography is often considered a feminist-inspired approach to social analysis and primarily considers women’s experiences within male- dominated societies and power structures. Smith’s work is seen to challenge sociology’s exclusion of women, both academically and in the study of women’s lives (Fenstermaker, n.d.).

Historically, social science research tended to objectify women and ignore their experiences except as viewed from the male perspective. Modern feminists note that describing women, and other marginalized groups, as subordinates helps those in authority maintain their own dominant positions (Social Sciences and Humanities Research Council of Canada n.d.). Smith’s three major works explored what she called “the conceptual practices of power” and are still considered seminal works in feminist theory and ethnography (Fensternmaker n.d.).

Sociological Research

The making of middletown: a study in modern u.s. culture.

In 1924, a young married couple named Robert and Helen Lynd undertook an unprecedented ethnography: to apply sociological methods to the study of one U.S. city in order to discover what “ordinary” people in the United States did and believed. Choosing Muncie, Indiana (population about 30,000) as their subject, they moved to the small town and lived there for eighteen months.

Ethnographers had been examining other cultures for decades—groups considered minorities or outsiders—like gangs, immigrants, and the poor. But no one had studied the so-called average American.

Recording interviews and using surveys to gather data, the Lynds objectively described what they observed. Researching existing sources, they compared Muncie in 1890 to the Muncie they observed in 1924. Most Muncie adults, they found, had grown up on farms but now lived in homes inside the city. As a result, the Lynds focused their study on the impact of industrialization and urbanization.

They observed that Muncie was divided into business and working class groups. They defined business class as dealing with abstract concepts and symbols, while working class people used tools to create concrete objects. The two classes led different lives with different goals and hopes. However, the Lynds observed, mass production offered both classes the same amenities. Like wealthy families, the working class was now able to own radios, cars, washing machines, telephones, vacuum cleaners, and refrigerators. This was an emerging material reality of the 1920s.

As the Lynds worked, they divided their manuscript into six chapters: Getting a Living, Making a Home, Training the Young, Using Leisure, Engaging in Religious Practices, and Engaging in Community Activities.

When the study was completed, the Lynds encountered a big problem. The Rockefeller Foundation, which had commissioned the book, claimed it was useless and refused to publish it. The Lynds asked if they could seek a publisher themselves.

Middletown: A Study in Modern American Culture was not only published in 1929 but also became an instant bestseller, a status unheard of for a sociological study. The book sold out six printings in its first year of publication, and has never gone out of print (Caplow, Hicks, & Wattenberg. 2000).

Nothing like it had ever been done before. Middletown was reviewed on the front page of the New York Times. Readers in the 1920s and 1930s identified with the citizens of Muncie, Indiana, but they were equally fascinated by the sociological methods and the use of scientific data to define ordinary people in the United States. The book was proof that social data was important—and interesting—to the U.S. public.

Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, engages in direct observation and even participant observation, if possible.

Researchers might use this method to study a single case of a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study as a method is that while offering depth on a topic, it does not provide enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.

However, case studies are useful when the single case is unique. In these instances, a single case study can contribute tremendous insight. For example, a feral child, also called “wild child,” is one who grows up isolated from human beings. Feral children grow up without social contact and language, which are elements crucial to a “civilized” child’s development. These children mimic the behaviors and movements of animals, and often invent their own language. There are only about one hundred cases of “feral children” in the world.

As you may imagine, a feral child is a subject of great interest to researchers. Feral children provide unique information about child development because they have grown up outside of the parameters of “normal” growth and nurturing. And since there are very few feral children, the case study is the most appropriate method for researchers to use in studying the subject.

At age three, a Ukranian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, and she ate raw meat and scraps. Five years later, a neighbor called authorities and reported seeing a girl who ran on all fours, barking. Officials brought Oxana into society, where she was cared for and taught some human behaviors, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2011). Case studies like this offer a way for sociologists to collect data that may not be obtained by any other method.

Experiments

You have probably tested some of your own personal social theories. “If I study at night and review in the morning, I’ll improve my retention skills.” Or, “If I stop drinking soda, I’ll feel better.” Cause and effect. If this, then that. When you test the theory, your results either prove or disprove your hypothesis.

One way researchers test social theories is by conducting an experiment , meaning they investigate relationships to test a hypothesis—a scientific approach.

There are two main types of experiments: lab-based experiments and natural or field experiments. In a lab setting, the research can be controlled so that more data can be recorded in a limited amount of time. In a natural or field- based experiment, the time it takes to gather the data cannot be controlled but the information might be considered more accurate since it was collected without interference or intervention by the researcher.

As a research method, either type of sociological experiment is useful for testing if-then statements: if a particular thing happens (cause), then another particular thing will result (effect). To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables.

Classically, the sociologist selects a set of people with similar characteristics, such as age, class, race, or education. Those people are divided into two groups. One is the experimental group and the other is the control group. The experimental group is exposed to the independent variable(s) and the control group is not. To test the benefits of tutoring, for example, the sociologist might provide tutoring to the experimental group of students but not to the control group. Then both groups would be tested for differences in performance to see if tutoring had an effect on the experimental group of students. As you can imagine, in a case like this, the researcher would not want to jeopardize the accomplishments of either group of students, so the setting would be somewhat artificial. The test would not be for a grade reflected on their permanent record of a student, for example.

And if a researcher told the students they would be observed as part of a study on measuring the effectiveness of tutoring, the students might not behave naturally. This is called the Hawthorne effect —which occurs when people change their behavior because they know they are being watched as part of a study. The Hawthorne effect is unavoidable in some research studies because sociologists have to make the purpose of the study known. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985).

A real-life example will help illustrate the process. In 1971, Frances Heussenstamm, a sociology professor at California State University at Los Angeles, had a theory about police prejudice. To test her theory, she conducted research. She chose fifteen students from three ethnic backgrounds: Black, White, and Hispanic. She chose students who routinely drove to and from campus along Los Angeles freeway routes, and who had had perfect driving records for longer than a year.

Next, she placed a Black Panther bumper sticker on each car. That sticker, a representation of a social value, was the independent variable. In the 1970s, the Black Panthers were a revolutionary group actively fighting racism. Heussenstamm asked the students to follow their normal driving patterns. She wanted to see whether seeming support for the Black Panthers would change how these good drivers were treated by the police patrolling the highways. The dependent variable would be the number of traffic stops/citations.

The first arrest, for an incorrect lane change, was made two hours after the experiment began. One participant was pulled over three times in three days. He quit the study. After seventeen days, the fifteen drivers had collected a total of thirty-three traffic citations. The research was halted. The funding to pay traffic fines had run out, and so had the enthusiasm of the participants (Heussenstamm, 1971).

Secondary Data Analysis

While sociologists often engage in original research studies, they also contribute knowledge to the discipline through secondary data analysis . Secondary data does not result from firsthand research collected from primary sources, but are the already completed work of other researchers or data collected by an agency or organization. Sociologists might study works written by historians, economists, teachers, or early sociologists. They might search through periodicals, newspapers, or magazines, or organizational data from any period in history.

Using available information not only saves time and money but can also add depth to a study. Sociologists often interpret findings in a new way, a way that was not part of an author’s original purpose or intention. To study how women were encouraged to act and behave in the 1960s, for example, a researcher might watch movies, televisions shows, and situation comedies from that period. Or to research changes in behavior and attitudes due to the emergence of television in the late 1950s and early 1960s, a sociologist would rely on new interpretations of secondary data. Decades from now, researchers will most likely conduct similar studies on the advent of mobile phones, the Internet, or social media.

Social scientists also learn by analyzing the research of a variety of agencies. Governmental departments and global groups, like the U.S. Bureau of Labor Statistics or the World Health Organization (WHO), publish studies with findings that are useful to sociologists. A public statistic like the foreclosure rate might be useful for studying the effects of a recession. A racial demographic profile might be compared with data on education funding to examine the resources accessible by different groups.

One of the advantages of secondary data like old movies or WHO statistics is that it is nonreactive research (or unobtrusive research), meaning that it does not involve direct contact with subjects and will not alter or influence people’s behaviors. Unlike studies requiring direct contact with people, using previously published data does not require entering a population and the investment and risks inherent in that research process.

Using available data does have its challenges. Public records are not always easy to access. A researcher will need to do some legwork to track them down and gain access to records. To guide the search through a vast library of materials and avoid wasting time reading unrelated sources, sociologists employ content analysis , applying a systematic approach to record and value information gleaned from secondary data as they relate to the study at hand.

Also, in some cases, there is no way to verify the accuracy of existing data. It is easy to count how many drunk drivers, for example, are pulled over by the police. But how many are not? While it’s possible to discover the percentage of teenage students who drop out of high school, it might be more challenging to determine the number who return to school or get their GED later.

Another problem arises when data are unavailable in the exact form needed or do not survey the topic from the precise angle the researcher seeks. For example, the average salaries paid to professors at a public school is public record. But these figures do not necessarily reveal how long it took each professor to reach the salary range, what their educational backgrounds are, or how long they’ve been teaching.

When conducting content analysis, it is important to consider the date of publication of an existing source and to take into account attitudes and common cultural ideals that may have influenced the research. For example, when Robert S. Lynd and Helen Merrell Lynd gathered research in the 1920s, attitudes and cultural norms were vastly different then than they are now. Beliefs about gender roles, race, education, and work have changed significantly since then. At the time, the study’s purpose was to reveal insights about small U.S. communities. Today, it is an illustration of 1920s attitudes and values.

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Open Education Sociology Dictionary

quantitative research

Table of Contents

Definition of Quantitative Research

( noun ) Using statistical analysis to quantify and measure social phenomenon, seeking to identify where possible causal relationships, then reporting the findings numerically.

Examples of Quantitative Research

statistical analysis
trend study

Quantitative Research Pronunciation

Pronunciation Usage Guide

Syllabification : quan·ti·ta·tive re·search

Audio Pronunciation

Phonetic Spelling

American English – /kwAHn-tuh-tay-tiv rEE-suhrch/
British English – /kwOn-ti-tuh-tiv ri-sUHRch/

International Phonetic Alphabet

American English – /ˈkwɑntɪˌteɪtɪv riˈsɜrʧ/
British English – /ˈkwɒntɪtətɪv rɪˈsɜːʧ/

Usage Notes

Plural: quantitative researches
Quantitative research is compared and contrasted to qualitative research.
Quantitative research is often viewed as reductionistic , whereas qualitative research is viewed as holistic. However, quantitative and qualitative research are complementary, not contradictory.
Reductively , quantitative research seeks to identify “how much” and “how often” and qualitative research seeks to explain the “how” and “why”.
Variant spelling: quantititive
quantitative analysis
quantitative data analysis
quantitative method
quantitative research method
quantitative sociology
Researchers ( adverb ) quantitatively study topic’s ( noun ) quantitativeness to determine the appropriate research method.

Additional Information

Quantitative Research Resources – Books, Journals, and Helpful Links
Word origin of “quantitative” and “research” – Online Etymology Dictionary: etymonline.com

Related Terms

reliability

Works Consulted

Andersen, Margaret L., and Howard Francis Taylor. 2011. Sociology: The Essentials . 6th ed. Belmont, CA: Wadsworth.

Carrabine, Eamonn, Pam Cox, Maggy Lee, Ken Plummer, and Nigel South. 2009. Criminology: A Sociological Introduction . 2nd ed. London: Routledge.

Ferris, Kerry, and Jill Stein. 2010. The Real World: An Introduction to Sociology . 2nd ed. New York: Norton.

Macionis, John, and Kenneth Plummer. 2012. Sociology: A Global Introduction . 4th ed. Harlow, England: Pearson Education.

Macmillan. (N.d.) Macmillan Dictionary . ( https://www.macmillandictionary.com/ ).

Marsh, Ian, and Mike Keating, eds. 2006. Sociology: Making Sense of Society . 3rd ed. Harlow, England: Pearson Education.

Merriam-Webster. (N.d.) Merriam-Webster Dictionary . ( http://www.merriam-webster.com/ ).

Oxford University Press. (N.d.) Oxford Dictionaries . ( https://www.oxforddictionaries.com/ ).

Schaefer, Richard. 2013. Sociology: A Brief Introduction . 10th ed. New York: McGraw-Hill.

Stolley, Kathy S. 2005. The Basics of Sociology . Westport, CT: Greenwood Press.

Wikipedia contributors. (N.d.) Wikipedia, The Free Encyclopedia . Wikimedia Foundation. ( https://en.wikipedia.org/ ).

Cite the Definition of Quantitative Research

ASA – American Sociological Association (5th edition)

Bell, Kenton, ed. 2013. “quantitative research.” In Open Education Sociology Dictionary . Retrieved May 26, 2024 ( https://sociologydictionary.org/quantitative-research/ ).

APA – American Psychological Association (6th edition)

quantitative research. (2013). In K. Bell (Ed.), Open education sociology dictionary . Retrieved from https://sociologydictionary.org/quantitative-research/

Chicago/Turabian: Author-Date – Chicago Manual of Style (16th edition)

Bell, Kenton, ed. 2013. “quantitative research.” In Open Education Sociology Dictionary . Accessed May 26, 2024. https://sociologydictionary.org/quantitative-research/ .

MLA – Modern Language Association (7th edition)

“quantitative research.” Open Education Sociology Dictionary . Ed. Kenton Bell. 2013. Web. 26 May. 2024. < https://sociologydictionary.org/quantitative-research/ >.

Types of Research in Sociology

In this section, you will find an overview of different research methods in sociology. You will find links to tools and resources in the library related to the different types of research and writing.

Qualitative vs Quantitative Research

What's the Difference?
Qualitative Research
Quantitative Research

Research in Psychology is categorized into two general methods:

Non-numerical evidence, usually examined in its raw form

Used when a researcher wants to understand people's opinions, idiosyncratic responses to an event, motivations, or underlying reasons for actions or decisions.

Learn about the Types of Qualitative Research Methods. link will open in a new window

Example: Interviewing the victims of a natural disaster to gather a range of emotional responses.

Numbers! Collected as numerical data or converted into numerical data and examined using statistical methods of analysis.

Used to examine trends and compare populations.

Learn about the Types of Quantitative Research Methods. link will open in a new window

Example: Asking victims of a natural disaster to rank their feelings of anxiety using a pre-determined scale.

When to use them

Psychological research is best when it uses complementary quantitative and qualitative approaches together in the same study, a method called triangulation.

Example: Observing parent-child interactions while watching tv then comparing those observations to measured rates of social and cognitive development in the children who participated in the study.

The Research Continuum

The researchers record data by studying participants at a distance. Researchers try not to influence the participants or their actions.

Types of observational studies include: Naturalistic Observation link will open in a new window , Participant Observation link will open in a new window , or Ethnography. link will open in a new window

The researcher will collect and write detailed accounts of individual lives. A case study can combine a few research approaches, including interviews, observational data, and archival data.

Examples of Case Studies include Freud's history of Anna O link will open in a new window ., and the stories related in Oliver Sacks's best selling book The Man Who Mistook his Wife for a Hat .

A researcher applies their own analytical model to data that has already been collected. They attempt to answer a new question or discover a new trend by looking at old data.

Typical sources of archival data include: census data link will open in a new window , court records will open in a new window , medical records, and even case files from other researchers.

Participants are asked a standard set of questions. These questions may be delivered in writing or through an interview format.

There are three main types of questionnaire methods: Random Sampling link will open in a new window , Stratified Sampling link will open in a new window , and Convenience Sampling link will open in a new window .

Researchers are trying to find a solution to an immediate, practical problem. Examples include reducing drug use or improving worker happiness.

Field research is a type of applied research that is undertaken in a non-laboratory setting. These settings may include a hospital or workplace.

Research conducted in a controlled environment. The results help scholars in the field to learn more about psychological processes such as cognition or emotional development.

Common Research Methods

Types of observational studies include: Non-Participant Observation window or Participant Observation .

A classic example of Case Studies in sociology is Erving Goffman's classic Asylums. link will open in a new window

Information is gathered one-on-one by asking questions orally. Structured Interviews can sometimes be used to gather quantitative data, because the structure allows the interview to function like a questionnaire.

More qualitative types of interviewing range from the Unstructured Interview which functions like a conversation based around a set list of topics, to the In-Depth Interview which may range widely with only a loose guide to direct it.

In-depth studies of groups in their natural setting. These studies utilize multiple type of research to create a multi-layered report. In addition to Participant Observation, a researcher may use interviews, questionnaires, or analysis of secondary research related to the group.

Some good examples of ethnographies available through the Library's online resources include: Recovery's Edge : An Ethnography of Mental Health Care and Moral Agency Link will open in a new window by Neely Laurenzo Meyers, Sex Work and the City Link will open in a new window by Ysmina Katsulis, and The breakup 2.0 : disconnecting over new media Link will open in a new window by Ilana Gershon.

Experimental Research Methods

What is Experimental Research?

Experimental Research is a sub-type of research in sociology. It may utilize the same methods as other research, but it differs in that it attempts measure variables as precisely as possible.

Experimental Research starts with a hypothesis and uses a variety of research methods to test that hypothesis. Ususally involves testing causal relationships.

Researchers study the cause and effect of variables in a natural setting , such as a classroom or workplace.

This allows the researcher to study participants or phenomena in their natural setting, so results might be more accurate . But they have less control over the variables, so results might not be as precise .

Research conducted in a controlled environment.

Participants' reactions may be influenced by the unnatural setting, but researchers have more control over variables.

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Research Methods: Quantitative and Qualitative Methods

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Sociological Research Methods: Qualitative and Quantitative Methods

Research methods and analysis of sociology dealt with techniques to obtain information in a vivid form.

Research is carefully observing patterns for searching for new facts or terms in any kind of subject. For example, there are several research centers for obtaining new results for better performance, say Bhabha Atomic Research center which specializes in nuclear fission and fusion reactions.

Sociologists Redman and Mory explained research work as a systematic way to earn new knowledge or say angle towards anything. For example, after a research work, various developments can be seen.

Research methods are categorized into Qualitative and Quantitative methods .

Quantitative methods included data structures, mathematical formulas, postulates, analysis by pie charts, graphical representations, Co-relation, Regression, etc. The methods used in Quantitative research will be studied in detail below.

Statistical data

Positivists majorly depend upon this method because they think it is the most convenient and efficient way to see society and its problems. For example, the rate of sex ratio or the number of rape happening in a particular area makes sociologists see the present scenario of the society.

Comparative Method

It can be easily guessed from the name itself that the method includes comparing different values. For example, in the science laboratory, there are comparators which compare different values of resistance and thus a mean value is written. Same is the case with sociology, different societies are compared by sociologist and after observing each and every factor they develop some theories under their research work. Marx, Durkheim , and Weber are said to be the inventor of this method which profoundly deals with the logic. The three of them compared many societies with each other to give some of the wonderful research work. Marx studied the phenomenon of difference and thus agreed that societies transform via many changes.

Durkheim observed the basis of division of labour and Weber tried to link the relation between capitalist and exploited countries. This method is still used by many sociologists for letting the world know about differences. For example, Michael Mann compared how every country differs when it comes to power and dominance. Devine showed the condition of workers in different time periods.

Field Methods

Science experiments are generally done in respective laboratories. But sociology experiments are performed in a natural arrangement outside the labs. For example, sociologists can carry out experiments in which they can observe people interaction ability thus categorizing them into introverts, ambivert, and extroverts. The advantage of this method is that it allows the expansion of areas where the experiment can be performed and better results are obtained as compared to other methods. But likewise, its biggest disadvantage is the variance can cause experiment results to differ unlike experiments performed in a science laboratory. This error is also termed as a Hawthorne effect. The experiments do not account for generalizing any theory as a particular amount of people can be tested.

Qualitative Methods are those methods which depend on the theories of Interactionism Theories. For example people way of talking under different circumstances studied by a researcher. The result will be completely based on the way the researcher perceives everything. The various methods of a Qualitative method are studied below.

Participant Observation

It can be seen as a modification of Field methods as this method involves the researcher too. The researcher has to keep a mindset as an observant which will decrease the chances of a biased opinion as the perception will not be compressed. The field researchers, data or any theory is studied comprehensively as a researcher and participant point of view.

Direct Observation

This method was one step up-gradation to field methods and Participant Observation. This observation also included a third party involvement whose perception cannot fall into the claws of a biased nature. For example, even if a researcher tries to complete experiment, he will not totally drench himself into the perception of the participant, thus a third person who will see the whole activity without any judgment will yield better results. For example in cricket matches, apart from umpires, a proper video is taken to see whether the player is out or not. This makes the judgment fair enough for everybody. In simple words, participant and researchers are not aware of the fact that they are being observed which accounts for natural reactions.

Unstructured Interviewing
These interviews are completely in contrast to conventionally structured interviews. They differ in various aspects. In unstructured interviewing, there are no set of standardized questions. The discussion can travel in any direction depending on the interviewer. Due to lack of patter, these interviews are hard to crack.
Case Studies

Case studies do not go along with a single method. There are various methods which are being used for observing even the minute details. It can be called as the summation of the direct method, unstructured interviews etc. The quantitative and qualitative approaches a given situation in an entirely different way. For example, quantitative methods are based on mathematical numbers, graphs, and statistics. But because of this method, much information is lost accounting for little information as compared to the qualitative method. Quantitative analysis is fact-driven but the facts can change anytime but they are mostly copied from earlier records, whereas qualitative analysis is observation-driven, its data can be changed accordingly which is its biggest advantage over the other.

TECHNIQUES OF DATA COLLECTION

Data collection is mainly stored in two ways, primary resources , and secondary resources .

Primary Resources are the data which are obtained by researchers, for example through personal or telephonic interviews, participant behaviour by keenly observing them or asking them a set of questions.

Secondary resources are the data which are mainly records in any form. For example, any old book can provide much information about the time period comes under secondary resources. There is no direct information but mainly statistics, graphs, old research works, or historical books.

MORE METHODS OF QUALITATIVE AND QUANTITATIVE ANALYSIS:-

Participant and Quasi-Participant Observation

It has been proved for a long time that observation helps in collecting data as well as result in accurate analysis. Observation contains two major functions viz. causes and effects. The observation is categorized in two ways viz. controlled and uncontrolled, active and passive.

Inactive observation, the researcher is also a part of an analysis. For example, he will take part in a game and will play fairly at his part.

In passive observation, the researcher observes everything from a distant place without getting noticed. For example mother-son duo small gestures can be easily noticed by him/her.

Controlled observations are those matter of solicitation in which things can be brought under control anytime. For example, knowing that someone is observing me I can easily change my reactions.

Uncontrolled observations are those observations in which neither researcher nor the people under observation stop the process of analysis. They are being adaptive to any situation no matter what results can be obtained.

There is another type called a Mixed Observation type. In these methods, extremities are found. Either the researcher is totally drenching in the activity or will be observing every bit in solitude. It is also known as Quasi Participant Observation.

This method involves a panel of interviewers and applicants. For example, in any placement drive, a panel is set up and they took a massive amount of information about the applicants by asking them many questions. Much information about their personality, IQ, confidence, abilities is judged in a matter of some minutes. The interviews can be of many types viz. formal, informal, solo or group.

Informal interviews are not much in trend but the other three are practised at a rapid rate.

Questionnaire

A questionnaire is a set of questions designed in a format which can be solved by only those who can read and write. Thus the biggest disadvantage of this method is that it cannot be fulfilled by everybody. The sole purpose of this method is storing answers and due to same questions, best answers manage to secure the position.

The schedule is entirely based on the way an interviewer seek things. The questionnaire set is solved by a person in front of the researchers. Thus the question does not affect much, but the perspective of the researcher does. There are many types of schedule:-

Rating Schedules – This kind of schedules generally come under the HR department. The opinions, ways of accepting or rejecting things, or habits are observed keenly.
Document Schedules – As the name suggests, it generally involves the paperwork. For example in criminology, criminal’s history is studied. Case studies are also popular, for example how to transform a city into the smart city.
Evaluation Schedules – Quantitative analysis for example data collection is a primary objective of this schedule. For example, if a company arrives at placement, the students collect every data, for example, the company position, job profile, CTC etc.
Observation Schedules – The researcher will observe everybody’s intention, either by involving in any activity or by being aloof.
Interview Schedules – The researcher freely asks respondents any question and after deciding their confidence, time to think, IQ etc is judged.

Continue Reading → Variable,Sampling,Hypothesis,Reliability & Validity

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Quantitative Methodology Research Paper

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History of Sociological Quantification

Quantitative reasoning is widely applied in the discipline of sociology and quantification aids sociologists in at least seven main research areas: quantitative modeling, measurement, sampling, computerization, data analysis, hypothesis testing, and data storage and retrieval. But sociologists differ widely in their views of the role of quantification in sociology. This has apparently always been true to some degree. While Durkheim was a proponent of quantification, Weber was less enthusiastic. However, while Weber advocated the nonquantitative method Verstehen, both Weber and Durkheim saw the importance of method as well as theory, as both authored books on method (Weber 1949; Durkheim [1938] 1964). Today, the situation is much different, as a wide gulf exits between theory and method in twenty-first-century sociology, with only a few authors such as Abell (1971, 2004) and Fararo (1989) simultaneously developing theory and quantitative methodology designed to test theoretical propositions.

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The most vocal proponent of quantification in sociology may have been Lundberg (1939), who was known as the unabashed champion of strict operationalism. Operationalism, as originally defined in physics by Bridgman (1948), is the belief that “in general any concept is nothing more than a set of operations, the concept is synonymous with the corresponding set of operations ” (Bridgman 1948:5–6). George Lundberg (1939, 1947) took the application of operationalism in sociology to an extreme. In Lundberg’s view, one did not approach an already existing concept and then attempt to measure it. The correct procedure in Lundberg’s view is to use measurement as a way of defining concepts. Thus, if one is asked what is meant by the concept of authoritarianism, the correct answer would be that authoritarianism is what an authoritarianism scale measures.

When he encountered objections to his advocacy of the use of quantification in sociology, Lundberg (1939, 1947) replied that quantitative concepts are ubiquitous in sociology, and need not even be symbolized by numerals, but can be conveyed verbally as well. For example, words such as “many,” “few,” or “several” connote quantitative concepts. In Lundberg’s view, quantification is embedded in verbal social research as well as in everyday thought and is not just an artificial construct that must be added to the research process by quantitative researchers.

After Lundberg (1939, 1947) and others such as Goode and Hatt (1952) and Lazarsfeld (1954) laid the foundation for quantitative sociology in the 1930s, 1940s, and 1950s, the field surged in the 1960s and 1970s. The 1960s saw increased visibility for quantitative sociology with the publication of books and articles such as Blalock’s (1960) Social Statistics, Kemeny and Snell’s (1962) Mathematical Models in the Social Sciences; White’s (1963) An Anatomy of Kinship; Coleman’s (1964) Introduction to Mathematical Sociology, Foundations of Social Theory; Duncan’s (1966) “Path Analysis: Sociological Examples”; Land’s (1968) “Principles of Path Analysis”; Blalock’s (1969) Theory Construction: From Verbal to Mathematical Formulations; and White’s (1970) Chains of Opportunity.

Quantitative methods became even more visible in the 1970s and 1980s with the publication of a host of mathematical and statistical works, including Abell’s (1971) Model Building in Sociology; Blalock’s (1971) Causal Models in the Social Sciences; Fararo’s (1973) Mathematical Sociology; Fararo’s (1989) Meaning of General Theoretical Sociology; Bailey’s (1974b) “Cluster Analysis”; and Blalock’s (1982) Conceptualization and Measurement in the Social Sciences.

Quantitative Data Collection

Specific quantitative techniques make rigorous assumptions about the kind of data that is suitable for analysis with that technique. This requires careful attention to data collection. For data to meet the assumptions of a quantitative technique, the research process generally entails four distinct steps: hypothesis formulation, questionnaire construction, probability sampling, and data collection.

Hypothesis Formulation

A hypothesis is defined as a proposition designed to be tested in the research project. To achieve testability, all variables in the hypothesis must be clearly stated and must be capable of empirical measurement. Research hypotheses may be univariate, bivariate, or multivariate, and some may contain auxiliary information, such as information about control variables. The vast majority of hypotheses used by quantitative sociologists are bivariate. The classical sequence is to formulate the hypotheses first, before instrument construction, sample design, or data collection. Hypotheses may be inductively derived during prior research (Kemeny and Snell 1962) or may be deductively derived (Bailey 1973). Increasingly, however, quantitative sociologists are turning to the secondary analysis of existing data sets. In such a case, hypothesis formulation can be a somewhat ad hoc process of examining the available data in the data bank or data set and formulating a hypothesis that includes the existing available variables.

For example, Lee (2005) used an existing data set and so was constrained to formulate hypotheses using the available variables. He presented three hypotheses, one of which stated that democracy is not directly related to income inequality (Lee 2005:162). While many quantitative studies in contemporary sociology present lists of formal hypotheses (usually five or less), some studies either leave hypotheses implicit or do not present them at all. For example, Torche (2005) discusses the relationship between mobility and inequality but does not present any formal hypotheses (p. 124).

Questionnaire Construction

In the classical research sequence, the researcher designed a questionnaire that would collect the data necessary for hypotheses testing. Questionnaire construction, as a middle component of the research sequence, is subject to a number of constraints that are not always well recognized. First and foremost is the necessity for the questionnaire to faithfully measure the concepts in the hypotheses. But other constraints are also imposed after questionnaire construction, chiefly sampling constraints, data-collection constraints, and quantitative data-analysis constraints. The questionnaire constrains the sampling design. If the questionnaire is very short and easily administered, this facilitates the use of a complicated sample design.

However, if the questionnaire is complex, then sample size may need to be reduced. The construction of a large and complex questionnaire means that it is difficult and time-consuming to conduct a large number of interviews. It also means that money that could otherwise be spent on the sample design must now be used for interviewer training, interviewing, and codebook construction. In addition to such sampling and data-collection constraints, the chief constraint on instrument design is the type of quantitative technique to be used for data analysis.

That is, the questionnaire must be designed to collect data that meet the statistical assumptions of the quantitative techniques to be used. Questionnaires can quickly become long and complicated. Furthermore, there is a tendency to construct closed-ended questions with not more than seven answer categories. While such nominal or ordinal data are often used in regression analyses, they are marginally inappropriate for ordinary least squares (OLS) regression and other quantitative techniques that assume interval or ratio data. Clearly, one of the great advantages of conducting a secondary analysis of data that has already been collected is that it avoids dealing with the many constraints imposed on the construction of an original datacollection instrument.

Probability Sampling

Many extant quantitative techniques (particularly inductive statistics) can only be used on data collected with a rigorous and sufficiently large probability sample, generally a random sample of some sort. One of the questions most frequently asked of research consultants is, “What is the minimum sample size acceptable for my research project?” Based on the law of large numbers and other considerations, some researchers permit the use of samples as small as 30 cases (Monette, Sullivan, and DeJong 2005:141). There is clearly a trend in the sociological literature toward larger sample sizes, often achieved through the use of the secondary analysis of existing samples and the pooling of multiple samples.

Sociology had few if any research methods books of its own prior to the publication of the volume by Goode and Hatt (1952). Before 1952, sociological researchers relied primarily on psychology research books, such as Jahoda, Deutsch, and Cook (1951), which de-emphasized sampling by relegating it to the appendix. Psychology emphasized the experimental method, with a small number of research subjects (often 15 or less), and de-emphasized surveys. Furthermore, in the mid-twentieth century, it was common for both psychology and sociology to use a “captive audience” sample of students from the researcher’s classes.

The chief research models for sociology before 1952 were psychology and (to a lesser degree) medicine. While psychology routinely used a small sample of subjects in experiments, samples in medical research were often quite small as well. If a researcher is conducting medical research, such as a study of pediatric obsessive compulsive disorder, it may be difficult to obtain more than 8 or 10 cases, as the onset of this syndrome is usually later in life. With psychology and medicine as its chief models before 1952, sample sizes in sociology tended to be small.

Over time, sample sizes in sociology have grown dramatically. The present emphasis is on national samples and multinational comparisons, as sociology moves away from the psychological model and toward the economic model. For example, Hollister (2004:669, table 1) did not collect her own data, but used secondary data with an N of 443, 399 to study hourly wages.

Data Collection

During the period 1950 to 1980 when social psychology was dominant in sociology, data collection was often a matter of using Likert scales of 5–7 categories (see Bailey 1994b) to collect data on concepts such as authoritarianism or alienation from a relatively small sample of persons.

Now that economics is becoming the dominant model (see Davis 2001), there are at least two salient ramifications of this trend. One is that an individual researcher is unlikely to possess the resources (even with a large grant) to collect data on 3,000 or more cases and so must often rely on secondary data, as did Joyner and Kao (2005). Another ramification is that researchers wishing to use these large economic data sets that are relatively prevalent must obviously use a different kind of data, and different quantitative techniques, than researchers did in an earlier era when psychology predominated. The psychological orientation resulted in data collection more conducive to analysis of variance, analysis of covariance, and factor analysis, in addition to multiple regression (OLS). Today things have changed, and the technique of choice for the large economic data sets is logistic regression.

Mathematical Sociology

It is useful to divide the extant quantitative techniques in twenty-first-century sociology into inferential statistics (probability-based techniques with tests of significance) and mathematical models (techniques that lack significance tests and are often nonprobabilistic). Rudner (1966) makes a distinction between method and methodology. Although the two terms are often used interchangeably in sociology and elsewhere, there is an important difference between them. According to Rudner, methods are techniques for gathering data, such as survey research, observation, experimentation, and so on. In contrast, methodologies are criteria for acceptance or rejection of hypotheses. This is a crucial distinction. Some mathematical models lack quantitative techniques for testing hypotheses, as these are not built into the model.

In contrast, inductive statistics, in conjunction with statistical sampling theory, provides a valuable means for sociologists not only to test hypotheses for a given sample but also to judge the efficacy of their inferences to larger populations. Tests of significance used in sociology take many forms, from gamma to chi-square to t -tests, and so on. Whatever the form or level of measurement, significance tests yielding probability, or “ p, ” values provide not only a way to test hypotheses but also a common element for community with researchers in other disciplines that also use significance tests.

Mathematical sociology has traditionally used methods such as differential and integral calculus (Blalock 1969: 88–109). Differential equations are frequently used to construct dynamic models (e.g., Kemeny and Snell 1962; Blalock 1969). However, one of the problems with mathematical models in sociology (and a problem that is easily glossed over) is that they are sometimes very difficult to apply and test empirically. Kemeny and Snell (1962) state that mathematical models are used to deduce “consequences” from theory, and that these consequences “must be put to the test of experimental verification” (p. 3). Since experimental verification in the strictest sense is relatively rare in sociology, this seems to be an Achilles heel of mathematical sociology.

To verify the predictions by comparing them with the experimental data, Kemeny and Snell (1962) use the statistical test chi-square. That is, the mathematical model proves inadequate for hypothesis testing and must be augmented by a statistical test (p. 62). Kemeny and Snell (1962) then “improve” the model by stating that there may be some subjects to which the model does not apply and “adding the assumption that some 20 per cent of subjects are of this type” (p. 62). Unfortunately, such “model simplification,” achieved by simply excluding a proportion of the population from the analysis, is rather common in quantitative sociology. Yamaguchi (1983) explains his failure to include women in the analysis by writing, “In this paper, I limit my analysis to non-black men to simplify the model” (p. 218).

The dilemma is real. If the sociological phenomenon is too complex, then the mathematical sociologist will not be able to solve all the inherent computational problems, even with a large computer. Fortunately, the future technological advances in computer hardware and software, along with the continued development of new mathematical techniques such as blockmodeling (Doreian, Batagelj, and Ferligoj 2005), ensure a bright future for mathematical sociology. While the challenges of social complexity are real, the rewards for those who can successfully model this complexity with mathematics are great. For additional commentary and references on mathematical sociology in the twenty-first century, see Edling (2002), Iverson (2004), Lewis-Beck, Bryman, and Liao (2004), Meeker and Leik (2000), and Raftery (2005).

Statistical Sociology

While statistical methods extant in sociology can all be classified as probability based, they can be divided into tests of significance (such as gamma) and methods used for explanation (often in terms of the amount of variance explained), prediction, or the establishment of causality. Among these techniques, the most commonly used are multiple correlation, multiple regression, logistic regression, as well as analysis of variance (the dominant method in psychology) or analysis of covariance. Other methods used less frequently by sociologists include cluster analysis, factor analysis, multiple discriminant analysis, canonical correlation, and smallest space analysis (Bailey 1973, 1974a), and latent class analysis (Uggen and Blackstone 2004).

Which statistical technique is appropriate for a given analysis can depend on a number of factors, one of which is the so-called level of measurement of the quantitative data involved. S. S. Stevens (1951) divided data into four distinct levels—nominal, ordinal, interval, and ratio. It is important to stress consistent measurement at all four levels, as lack of attention to consistent measurement across studies in sociology is problematic for the field.

The reality is that nominal variables can be very important in both sociological theory and statistics, but unfortunately they have been badly neglected by sociologists and often are created and treated in a haphazard fashion. This is unfortunate because discussions of classification techniques are readily available to sociologists in the form of work on cluster analysis and various classification techniques for forming typologies and taxonomies (McKinney 1966; Bailey 1973, 1994a). Carefully constructed classification schemas can form the foundation for all “higher” levels of measurement. A sociological model lacking adequate nominal categories can be the proverbial house of cards, ready to collapse at any moment.

The nominal level of measurement deals with nonhierarchical categories. Many of the most theoretically important and frequently used sociological variables lie at this level of measurement, including religion, sex, political affiliation, region, and so on. Much of the statistical analyses at the nominal level consist of simple frequency, percentage, and rate analysis (Blalock 1979). However, the chi-square significance test can be used at the nominal level, as can a number of measures of association, such as Tschuprow’s T, V, C, Tau, and Lambda (Blalock 1979:299–325). Sociologists often dislike nominal categorical variables because it is felt that they are merely descriptive variables that do not possess the explanatory and predictive power of continuous variables, such as interval and ratio variables. But more important, nominal (and also ordinal) categorical variables are disliked because they generally do not fit into the classical multiple regression (OLS) models that (until the recent dominance of logistic regression) have been widely used in sociology.

In univariate cases with a large number of categories, or especially in multivariate cases with a large number of variables, and with each containing a large number of categories, the analysis can quickly become very complex, so that one is dealing with dozens if not hundreds of categories. As Blalock (1979) notes, there is often a tendency for researchers to simplify the analysis by dichotomizing variables (p. 327). Unfortunately, such attenuation results in both loss of information and bias.

Another problem with categorical data is that the printed page is limited to two dimensions. Thus, if one has as few as five categorical variables, and wishes to construct a contingency table showing their interrelations, this requires a five-dimensional table, but only two dimensions are available. The customary way to deal with this, even in computer printouts, is to print 10 bivariate tables, often leading to an unmanageable level of complexity.

Nominal and ordinal variables share some similarities and problems. Measures of association such as Spearman’s r s and tests of significance such as the Wilcoxon test are also available for ordinal variables (Blalock 1979). As with nominal variables, ordinal variables cannot be added, subtracted, multiplied, or divided (one cannot add rank 1 to rank 2 to obtain rank 3).

The ordinal level shares with the nominal level the problem of the desire to simplify. Sociologists often wish to reduce the number of ordered categories to simplify the research project, but unfortunately they often conduct this simplification in an ad hoc manner, without any statistical or theoretical guidelines for reducing the number of categories. Again, this leads to problems of attenuation and bias, as noted for the nominal level.

Interval and Ratio

A sea change has occurred in sociology in the last 40 years, as shown later in the review of American Sociological Review ( ASR ) . During the 1950s and 1960s, American sociologists relied primarily on percentage analysis, often using nominal and ordinal measurement. Later in the twentieth century, quantitative researchers stressed the use of interval and ratio variables to meet the assumptions of OLS multiple regression analysis. Now, as seen below, there has been a major shift back to the use of nominal and ordinal variables in logistic regression.

Interval variables are continuous, with “arbitrary” zero points, while ratio variables have absolute or “nonarbitrary” zero points. Theoretically, only ratio variables, and only those found in nonattenuated fashion with a wide range of continuous values, should be used in multiple regression models, either as independent or dependent variables. Although textbooks such as Blalock (1979) say that only interval measurement is needed, in my opinion ratio is preferred and should be used whenever possible (p. 382). In reality, continuous variables are routinely used in regression without testing to see whether they can be considered ratio or only interval.

Furthermore, while such continuous variables may theoretically or potentially have a wide range of values, they often are empirically attenuated, with extremely high and low values (or perhaps even midrange values) occurring infrequently or rarely. Also, attenuated variables that are essentially ordinal, and contain only five values or so, are often used in surveys (e.g., Likert scales). While these Likert variables do not meet the technical requirements of multiple regression, either as dependent or independent variables, they are often used in regression, not only as independent variables but also as dependent variables.

As noted earlier, sociologists have traditionally struggled to meet the requirements of OLS regression, especially when encountering so many nominal and ordinal variables in everyday theory and research. For example, Knoke and Hout (1974) described their dependent variable (party identification) by saying, “The set of final responses may be coded several ways, but we have selected a fivepoint scale with properties close to the interval scaling our analysis requires” (p. 702). While this dependent variable may indeed be “close” to interval, it remains severely attenuated, possessing only five “points” or values compared with the hundreds or even thousands of potential values in some interval variables. In addition to using attenuated ordinal scales in regression (even though they clearly do not meet the assumptions of regression), sociologists often use nominal variables in regression. These are often used as predictors (independent variables) through the technique of “dummy variable analysis” involving binary coding.

As shown later by my review of ASR, the most common statistical technique in contemporary sociology is multiple regression in some form, including OLS and logistic regression. However, many of the variables used in sociology are nominal or ordinal. Those that are interval or ratio are often recoded as ordinal variables during data collection. The result is that between the existence of “naturally occurring” nominal and ordinal variables and the (often unnecessary) attenuation of nominal, ordinal, interval, and ratio variables, the range of empirical variation is greatly attenuated.

A common example is when an income variable with potentially dozens or even hundreds of values is reduced to five or so income categories to make it more manageable during the survey research process (see Bailey 1994b).

While it is true that respondents are often reluctant to provide their exact income, other alternatives to severe category attenuation are available. These include the use of additional categories (up to 24) or even the application of techniques for dealing with missing data. In addition, some common dependent variables, when studied empirically, are found to have small empirical ranges, but the adequacy of correlation and regression is formally assessed in terms of the degree of variance explained. Considering the cumulative effect of variables that are empirically attenuated, added to those variables that are attenuated by sociologists during the course of research, it is not surprising that explained variance levels are often disappointing in sociology.

A generic multiple regression equation for two independent variables is shown in Equation 10.1.

Y = a + b 1 X 1 + b 2 X 2 [10.1]

The model in Equation 10.1 is quite robust and adaptable but should not be abused by using it with severely attenuated data. Although one cannot add additional dependent variables, additional independent variables are easily added. Also, the model can easily be made nonlinear by using multiplicative predictors such as X 1 X 2 or X n .

Assume that the dependent variable ( Y ) is annual income, and the predictors are, respectively, age and educational level. One could conduct an OLS regression analysis for a large data set and experience a fairly small degree of attenuation if the data were collected properly and the variables were not attenuated through unnecessary categorization. But now assume that a second regression analysis is computed on Equation 10.1, but this time the dependent variable is whether the person attends college or not, coded 1 or 0, and the independent variables are sex (coded 1 for female and 0 for male) and age (coded 1 for 20 or younger and 0 for 21 or older). Running OLS regression on this will yield very little in terms of explained variance. The analysis can be converted to logistic regression by computing the odds ratio and taking the natural log (logit) to make it linear. The limitations of this model are that little variance exists to be explained and the predictors are inadequate.

Implications

While many of the logistic regressions one sees in the sociological literature have many more predictors, many of these are often dummy variables (ordinal or ratio), and the wisdom of running regression on such data remains debatable. What accounts for the tremendous popularity of logistic regression, when many times the degree of variance explained remains decidedly unimpressive (see the discussion below)? Perhaps logistic regression is now a fad, or perhaps users do not see an adequate alternative. Why do they not just present correlation matrices? Why is regression needed? Perhaps because typologies using nominal variables are said to provide description, correlation is said to provide explanation, and regression is said to provide prediction, with prediction considered to be the highest form of analysis (Blalock 1979).

The implications of the analysis to this point are clear: Sociologists have long struggled to deal with the analytical problems posed by the different levels of measurement, and they continue to do so. While the recent widespread adoption of logistic regression has surely changed the way that sociologists deal with nominal (and to a lesser extent ordinal) variables, for example, it is not clear that the fit between theory and method, or between empirical data and method, has been drastically improved. Changes are still needed, and some recommendations are presented below.

Method and Theory

As previously noted, method and theory have become sharply bifurcated within sociology over the past 40 years. While the ASR once published methods articles, now these articles are routinely segregated into journals, such as Sociological Methodology, Sociological Methods and Research, or the Journal of Mathematical Sociology. Thus, quantitative methods are not only separated from qualitative sociology (which has its own journals such as Qualitative Sociology ) but also are separated from sociological theory (with its own American Sociological Association journal, Sociological Theory ).

Kemeny and Snell (1962) state that one first inductively derives a theory through observation and empirical research and then uses quantitative models to deduce testable hypotheses from the theory. The procedure suggested by Kemeny and Snell (1962) is a sound one. The obvious problem with successfully using such an integrated theory/method research process in contemporary sociology is that the theory and quantitative methods knowledge segments are so segregated and widely divided that it is increasingly difficult for the individual researcher to have access to all of this separated literature. By segregating sociology into largely verbal theory ( Sociological Theory) and quantitative sociology (the Journal of Mathematical Sociology ), the process of developing theories and testing them is made more difficult than it should be.

In spite of the wide degree of artificial separation of theory and method in sociology, the quantitative area has changed in a manner that makes it more consistent with the needs of theory. To meet the goal of operationalizing sociological theory, the quantitative method area should minimally provide three main services:

Quantitative sociology must provide both diachronic (dynamic) models dealing with process and synchronic (cross-sectional) models dealing with structure. Until the last decade or so, statistical sociology provided mainly synchronic or cross-sectional models via OLS. Now many logistic regression models are longitudinal as in event history analysis (Allison 1984).
The second service that quantitative method (including both statistical sociology and mathematical sociology) must provide is to talk increasingly in terms of actors rather than primarily in terms of equations or variables. While theory talks in terms of action by individuals or groups (agency), quantitative method talks in terms of change in variables (mathematics) or relationships among sets of variables (regression). A good example of the use of actor-oriented dependent variables in logistic regression is provided by Harknett and McLanahan (2004) who predict whether the baby’s mother will take a certain action or not (marry the baby’s father within 30 days).
Quantitative sociology must do a better job of raising R 2 s as variance explained in many regression analyses in sociology (whether OLS or logistic regression) remains unacceptably low. A lot of this may be due to attenuation of variables, both dependent and independent. As seen above, some of the attenuation is avoidable, and some unavoidable. Until recently, the dominant regression model was OLS regression, which did a poor job of incorporating nominal and ordinal variables. Logistic regression includes nominal variables aggressively, thus making it more compatible with theory that is replete with such nominal variables and providing a welcome means of bridging the theory-method gap. However, it is unclear that the incorporation of nominal variables (both dependent and independent) in logistic regression has raised the variance explained by any meaningful degree. It is important that we pay more attention to this problem and that we focus on R 2 values, not just on p That is, it is likely that there is actually more variance that can be explained empirically, but the techniques in use are not picking it all up. Perhaps sociology has lost sight of whether sociological models fit the data well, which is the primary point of prediction. To say it another way, if logistic regression is used in virtually every analysis in the ASR, it seems obvious that this method will fit the data better in some cases than in others. In the cases where it can be determined that the fit is not good, perhaps an alternative method of analysis should be considered.

Historical Comparisons

Perhaps most sociologists are at least vaguely aware of changes in quantitative techniques that have appeared in the sociological literature in the last 40 years, particularly the shift toward logistic regression. I decided that it would be helpful to illustrate these changes by conducting a review of the ASR over the last 40 years. While a full review of all issues was impossible due to time constraints, it seemed that a partial review would be illuminating. I compared the last full volume of the ASR that was available (2004) with the volumes 40 years before (1964), and 30 years before (1974), as shown in Table 1.

Table 1 shows the presence or absence of quantitative analysis in every article of ASR in 1964 (Volume 29), 1974 (Volume 39), and 2004 (Volume 69). These volumes were not selected by scientific probability sampling but were arbitrarily chosen to reflect changes in quantitative methods. The first year (1964) shows the initial use of regression, 1974 shows the growth of OLS regression, and 2004 (the last full volume available) shows the dominance of regression, both the continuing presence of OLS and the predominance of logistic regression. Presidential addresses were omitted as they tended to be nonquantitative essays. I also omitted research notes, replies, and comments and included only the articles from the main research section of the journal.

The first row of Table 1 analyzes Volume 29 (1964) of ASR. It reveals that 70 percent of all articles (28 out of 40) were quantitative. The remaining 12 were verbal essays without any numbers. An article was counted as quantitative if it had raw scores or means. The predominant numerical method in 1964 was percentage analysis; however, there were two cases of regression analysis. These were OLS analyses with continuous dependent variables, although they were identified only as “regression analysis.” There were no instances of logistic regression. Although regression was soon to dominate sociological statistics, this trend was not yet evident in 1964.

However, by 1974, the trend toward the use of regression was clearly visible. The proportion of the articles that were quantitative in 1974 was 86 percent, up from 70 percent a decade earlier. Although there were still no logistic regression analyses in ASR in 1974 (regression with categorical dependent variables), fully 49 percent of all quantitative articles (and 42 percent of all articles in the entire volume) were OLS regressions showing clear evidence of its upcoming dominance in sociological analysis.

It should be noted that in 1974, many of the OLS regression analyses were presented in the form of “path analysis,” with the “path coefficients” presented in path diagrams. While 70 percent of all ASR articles were quantitative in 1964 and 86 percent in 1974, by 2004 the proportion of quantitative ASR articles had climbed to a startling 95 percent, with logistic regression in some form accounting for the majority of these. Out of a total of 37 articles in Volume 69, only two were entirely verbal, lacking any numerical analysis at all.

Even more startling was the fact that in 2004, out of the 35 quantitative articles in ASR, 32, or 86 percent of all articles in the volume, and 91 percent of all quantitative articles were regressions. Still more surprising, of the 32 articles with regressions, only three had OLS regression only. The remaining 29 had logistic regression, with 25 of these containing logistic regression only, and with four more articles presenting both OLS and logistic regression in the same article. Four additional articles (not shown in Table 1) contained “hybrid” models, which used various combinations of OLS and logged dependent variables, or presented models said to be “equivalent to OLS,” and so on. Of the three quantitative articles that contained no regression, one contained both analysis of variances and analysis of covariance, while the other two contained only percentage analysis.

When logistic regression occurs in 29 out of 35 (83 percent) of quantitative articles and 29 out of 37 total articles (78 percent), it obviously has an amazing degree of dominance for a single technique. In fact, in the last four issues of Volume 29 (Issues 3, 4, 5, and 6), 19 of the total of 20 articles contained logistic regression of some sort (the other article was entirely verbal, with no quantitative analysis of any kind). This means that fully 100 percent of the quantitative articles (and 95 percent of all articles) in the June through December issues of the 2004 ASR (Volume 69) contained at least one logistic regression analysis. This dominance prompts the rhetorical question of whether one can realistically hope to publish in ASR without conducting logistic regression. It appears possible, but the odds are against it. If one wishes to publish in ASR without logistic regression analysis, the article should include OLS regression.

What accounts for the fact that in 2004, 95 percent of all published ASR articles were quantitative, and of these, 83 percent contained at least one logistic regression analysis? Could it be that quantitative sociologists in general are taking over the field of sociology, and sociologists should expect a wave of mathematical sociology articles to be published in ASR? I did not see any publications in Volume 69 containing articles that I would classify as mathematical sociology. I did see two models in 1974 that I would classify as work in mathematical statistics (one stochastic model and one Poisson model), but none in 2004.

Comparing 1974 ASR articles with 2004 ASR articles, we see a sea change toward logistic regression. From the standpoint of quantitative methodology, I can certainly appreciate the heavy reliance that ASR currently has on logistic regression. While casual observers might say that “regression is regression” and that not much has changed in 30 years, in reality nothing could be farther from the truth. The 29 logistic regression analyses presented in Volume 69 of ASR differ from the 25 OLS regression analyses of Volume 39 in a number of important ways. The traditional OLS regression that was dominant in 1974 has the following features:

It uses a continuous (internal or ratio) dependent variable.
It uses predominantly continuous independent variables, perhaps with a few dummy variables.
It uses R 2 to evaluate explanatory adequacy in terms of the amount of variance explained.
It uses about 5 to 10 independent variables.
It usually reports values of R 2 (explained variance) in the range of .20 to .80, with most values being in the intermediate lower part of this range.

In contrast, the logistic regression that dominates twenty-first-century sociology has these features:

It uses categorical rather than continuous dependent variables (see Tubergen, Maas, and Flap 2004).
It often uses rather ad hoc procedures for categorizing dependent and independent variables, apparently without knowledge of proper typological procedures (Bailey 1994a) and without regard to the loss of information that such categorization entails, as pointed out by Blalock (1979). Some of these decisions about how categories should be constructed may be theory driven, but many appear to be arbitrary and ad hoc categorizations designed to meet the specifications of a computerized model.
It logs the dependent variable to “remove undesirable properties,” generally to achieve linearity, and to convert an unlogged skewed distribution to a logged normal distribution, more in keeping with the requirements of regression analysis (see Messner, Baumer, and Rosenfeld 2004).
It uses more categorical or dummy variables as independent variables, on average, than does OLS regression.
It uses larger samples.
It uses more “pooled” data derived through combining different samples or past studies. This has the advantage of getting value from secondary data. While it is good to make use of data stored in data banks, in some cases this practice may raise the question of whether the data set is really the best one or is just used because it is available.
It uses more models (often three or more) that can be compared in a single article.
It uses more multilevel analysis.
It uses more “corrections” of various sorts to correct for inadequacies in the data.
It often does not report R 2 because it is generally recognized to have “undesirable properties” (see Bailey 2004), thereby providing no good way for evaluating the efficiency of the explication in terms of the amount of variance explained.
It generally reports statistically significant relationships with p values less than .05, and often less than .01, or even .001.
It presents more longitudinal analysis.

While the trends toward multilevel analysis, longitudinal analysis, and actor orientation are welcome, the plethora of categorical variables and the complexity of the presentations (often spilling over into online appendixes) are of concern. Also, while all computerized statistical programs are vulnerable to abuse, the probability that some of the “canned” logistic regression programs will be used incorrectly seems high due to their complexity. But the chief concern regarding the dominance of logistic regression is that while the recent logistic regressions appear more sophisticated than their traditional OLS counterparts, it is not clear that they have provided enhanced explanatory power in terms of variance explained. In fact, logistic regression in some cases may have lowered the explanatory efficacy of regression, at least when interpreted in terms of explained variance.

The binary coding of dependent and independent variables can obviously lead to extreme attenuation and loss of explanatory power, as noted by Blalock (1979). One of the most undesirable properties of R 2 for any dichotomous analysis is that the dichotomous dependent variable is so attenuated that little variance exists to be explained and so R 2 is necessarily low. If nothing else, the large number of cases when no R 2 of any sort is reported is certainly a matter of concern, as it makes it very difficult to compare the adequacy of OLS regressions with the adequacy of logistic regressions.

In lieu of R 2 , users of logistic regression generally follow one of three strategies: (1) They do not report any sort of R 2 (Hollister 2004:670), relying solely on p values. The p values of logistic regression often are significant due (at least in part) to large sample size, such as Hollister’s (2004:669, sample N of 443,399 in table 1). While large sample sizes may not guarantee significant p values, they make them easier to obtain than with the smaller sample sizes previously used in many traditional sociological studies; (2) they report a “pseudo R 2 ” (see Hagle 2004), such as those reported by McLeod and Kaiser (2004:646) for their table 3, ranging in value from .017 to .112 (the highest reported in the article is .245 in table 5, p. 648); or (3) they report some other R 2 term, such as the Nagelkerke R 2 , as reported by Griffin (2004:551), in his table 4, with values of .065 and .079.

In the middle of the twentieth century, sociology relied on careful percentage analysis as the backbone of its quantitative methodology, augmented by relatively rudimentary statistics, such as measures of central tendency, correlation coefficients, and tests of significance such as chi-square. Although sociologists were aware of multivariate statistics such as factor analysis and multiple discriminant analysis, the onerous computation that these methods required before computerization limited their use.

With the advent of mainframe computers in the 1960s and 1970s, sociologists could go to their universitycomputing center and run a variety of multivariate statistical analyses. Thus, by 1974, OLS regression became the dominant method. A major problem with OLS regression was that it could accommodate only a single intervaldependent variable, and the independent variables had to be intervally measured as well, except for “dummy” variables. Thus, many important theoretical variables, such as religion, race, gender, and so on, could not be properly accommodated in the dominant regression model.

But by 2004, all had changed. The sea change to logistic regression facilitated the use of multiple regression, as one no longer needed to limit the analysis to interval or ratio dependent variables. Also, the dependent variable could be logged. The advantages of logistic regression are great. These advantages include the facilitation of multilevel analysis (such as use of the individual and country levels) and the ease with which data can be pooled so that many surveys are used and sample sizes are large. Logistic regression makes good use of existing data sets and does a much better job of longitudinal analysis than OLS. Furthermore, the published logistic regressions are replete with categorical variables that were previously missing from OLS regression.

While the advantages of logistic regression are obvious, it may be debatable whether the dominance of this technique indicates that theory and method have merged in an ideal fashion in contemporary sociology. There are several reasons why. First, much sociological theory is not stated in terms of the binary-coded dichotomies favored in logistic regression. While the prediction of dichotomies is certainly theoretically significant in some cases, it would not seem to match the general significance of predicting the full range of values in an interval or ratio variable. That is, why limit the analysis to predicting 1 or 0, when it is possible to predict age from birth to death. Second, since sociological theory is generally not written in terms of logged variables, it is difficult to interpret statistical analysis where the dependent variables are logged to normalize them.

In summary, the logistic regression analyses now dominating provide a number of benefits. These include, among others, advances in longitudinal analysis, in multilevel analysis, in the use of pooled data, in the presentation of more comparative models in each analysis, and in the presentation of more interaction analyses. But logistic regression sometimes appears to relinquish these gains by losing theoretical power when it is unable to provide impressive R 2 values. This is due in part to the excessive attenuation resulting from the widespread use of binarycoded dependent variables (often dichotomies).

Prospects for the 21st Century

The future for quantitative sociology will include the continued use of logistic regression. There also will be further developments in blockmodeling and also in longitudinal methods, including event history analysis. There will also be continued interest in multilevel techniques (Guo and Zhao 2000) as well as in agent-based or actor modeling (Macy and Willer 2002). There will also be increased interest in nonlinear analysis (Meeker and Leik 2000; Macy and Willer 2002). In addition, there will be continued advances in regression analysis in such areas as fixed effects regression, including Cox regression (Allison 2005) and spline regression (Marsh and Cormier 2001).

Davis (2001) writes, “In sum, I believe the seeming technical progress of logistic regression (and its cousins) is actually regressive” (p. 111). In another analysis of the logistic regression model, Davis writes,

In short, despite the trappings of modeling, the analysts are not modeling or estimating anything; they are merely making glorified significance tests. Furthermore, these are usually merely wrong or deceptive significance tests because . . . they usually work with such large Ns that virtually anything is significant anyway. (P. 109)

Davis recommends a return to path analysis, in part because it is easier to measure the success or failure of path analysis (p. 110).

Sociologists rely on logistic regression because the variables used are conducive to this technique. Davis (2001) also notes the shift within sociology from using psychology as a model to the present reliance on economics. He writes that in the 1950s psychology was the “alpha animal,” but now economics is a “Colossus” (p. 105). Quantitative researchers have long favored economic variables because they are easier to quantify. Furthermore, inequality research has benefited from the wide availability of economic coefficients such as the Gini (Lee 2005). Nevertheless, sociologists are now more likely to be citing Econometrica or The World Bank Economic Review, and the future influence of economics on sociology seems clear.

While the advantages of logistic regression are clear, there are other methods that deserve consideration as well. It is clear that sociologists will increasingly employ the methods of epidemiology, such as hazard and survival models and Cox regression (Allison 2005), and the methods and data sets of economics. But in addition, sociologists will undoubtedly continue to collect their own data sets while employing the OLS regression and path analysis models. They will also use relatively neglected techniques such as factor analysis, analysis of variance, analysis of covariance, multiple discriminate analysis, canonical correlation, and smallest space analysis.

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Types of market research: Methods and examples

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Here at GWI we publish a steady stream of blogs, reports, and other resources that dig deep into specific market research topics.

But what about the folks who’d appreciate a more general overview of market research that explains the big picture? Don’t they deserve some love too?

Of course they do. That’s why we’ve created this overview guide focusing on types of market research and examples. With so many market research companies to choose from, having a solid general understanding of how this sector works is essential for any brand or business that wants to pick the right market research partner.

So with that in mind, let’s start at the very beginning and get clear on…

Market research definition

At the risk of stating the slightly obvious, market research is the gathering and analyzing of data on consumers, competitors, distributors, and markets. As such it’s not quite the same as consumer research , but there’s significant overlap.

Market research matters because it can help you take the guesswork out of getting through to audiences. By studying consumers and gathering information on their likes, dislikes, and so on, brands can make evidence-based decisions instead of relying on instinct or experience.

What is market research?

Market research is the organized gathering of information about target markets and consumers’ needs and preferences. It’s an important component of business strategy and a major factor in maintaining competitiveness.

If a business wants to know – really know – what sort of products or services consumers want to buy, along with where, when, and how those products and services should be marketed, it just makes sense to ask the prospective audience.

Without the certainty that market research brings, a business is basically hoping for the best. And while we salute their optimism, that’s not exactly a reliable strategy for success.

What are the types of market research?

Primary research .

Primary research is a type of market research you either conduct yourself or hire someone to do on your behalf.

A classic example of primary research involves going directly to a source – typically customers or prospective customers in your target market – to ask questions and gather information about a product or service. Interviewing methods include in-person, online surveys, phone calls, and focus groups.

The big advantage of primary research is that it’s directly focused on your objectives, so the outcome will be conclusive, detailed insights – particularly into customer views – making it the gold standard.

The disadvantages are it can be time-consuming and potentially costly, plus there’s a risk of survey bias creeping in, in the sense that research samples may not be representative of the wider group.

Secondary research

Primary market research means you collect the data your business needs, whereas the types of market research known as secondary market research use information that’s already been gathered for other purposes but can still be valuable. Examples include published market studies, white papers, analyst reports, customer emails, and customer surveys/feedback.

For many small businesses with limited budgets, secondary market research is their first choice because it’s easier to acquire and far more affordable than primary research.

Secondary research can still answer specific business questions, but with limitations. The data collected from that audience may not match your targeted audience exactly, resulting in skewed outcomes.

A big benefit of secondary market research is helping lay the groundwork and get you ready to carry out primary market research by making sure you’re focused on what matters most.

Qualitative research

Qualitative research is one of the two fundamental types of market research. Qualitative research is about people and their opinions. Typically conducted by asking questions either one-on-one or in groups, qualitative research can help you define problems and learn about customers’ opinions, values, and beliefs.

Classic examples of qualitative research are long-answer questions like “Why do you think this product is better than competitive products? Why do you think it’s not?”, or “How would you improve this new service to make it more appealing?”

Because qualitative research generally involves smaller sample sizes than its close cousin quantitative research, it gives you an anecdotal overview of your subject, rather than highly detailed information that can help predict future performance.

Qualitative research is particularly useful if you’re developing a new product, service, website or ad campaign and want to get some feedback before you commit a large budget to it.

Quantitative research

If qualitative research is all about opinions, quantitative research is all about numbers, using math to uncover insights about your audience.

Typical quantitative research questions are things like, “What’s the market size for this product?” or “How long are visitors staying on this website?”. Clearly the answers to both will be numerical.

Quantitative research usually involves questionnaires. Respondents are asked to complete the survey, which marketers use to understand consumer needs, and create strategies and marketing plans.

Importantly, because quantitative research is math-based, it’s statistically valid, which means you’re in a good position to use it to predict the future direction of your business.

Consumer research

As its name implies, consumer research gathers information about consumers’ lifestyles, behaviors, needs and preferences, usually in relation to a particular product or service. It can include both quantitative and qualitative studies.

Examples of consumer research in action include finding ways to improve consumer perception of a product, or creating buyer personas and market segments, which help you successfully market your product to different types of customers.

Understanding consumer trends , driven by consumer research, helps businesses understand customer psychology and create detailed purchasing behavior profiles. The result helps brands improve their products and services by making them more customer-centric, increasing customer satisfaction, and boosting bottom line in the process.

Product research

Product research gives a new product (or indeed service, we don’t judge) its best chance of success, or helps an existing product improve or increase market share.

It’s common sense: by finding out what consumers want and adjusting your offering accordingly, you gain a competitive edge. It can be the difference between a product being a roaring success or an abject failure.

Examples of product research include finding ways to develop goods with a higher value, or identifying exactly where innovation effort should be focused.

Product research goes hand-in-hand with other strands of market research, helping you make informed decisions about what consumers want, and what you can offer them.

Brand research

Brand research is the process of gathering feedback from your current, prospective, and even past customers to understand how your brand is perceived by the market.

It covers things like brand awareness, brand perceptions, customer advocacy, advertising effectiveness, purchase channels, audience profiling, and whether or not the brand is a top consideration for consumers.

The result helps take the guesswork out of your messaging and brand strategy. Like all types of market research, it gives marketing leaders the data they need to make better choices based on fact rather than opinion or intuition.

Market research methods

So far we’ve reviewed various different types of market research, now let’s look at market research methods, in other words the practical ways you can uncover those all-important insights.

Consumer research platform

A consumer research platform like GWI is a smart way to find on-demand market research insights in seconds.

In a world of fluid markets and changing attitudes, a detailed understanding of your consumers, developed using the right research platform, enables you to stop guessing and start knowing.

As well as providing certainty, consumer research platforms massively accelerate speed to insight. Got a question? Just jump on your consumer research platform and find the answer – job done.

The ability to mine data for answers like this is empowering – suddenly you’re in the driving seat with a world of possibilities ahead of you. Compared to the most obvious alternative – commissioning third party research that could take weeks to arrive – the right consumer research platform is basically a magic wand.

Admittedly we’re biased, but GWI delivers all this and more. Take our platform for a quick spin and see for yourself.

And the downside of using a consumer research platform? Well, no data set, however fresh or thorough, can answer every question. If you need really niche insights then your best bet is custom market research , where you can ask any question you like, tailored to your exact needs.

Face-to-face interviews

Despite the rise in popularity of online surveys , face-to-face survey interviewing – using mobile devices or even the classic paper survey – is still a popular data collection method.

In terms of advantages, face-to-face interviews help with accurate screening, in the sense the interviewee can’t easily give misleading answers about, say, their age. The interviewer can also make a note of emotions and non-verbal cues.

On the other hand, face-to-face interviews can be costly, while the quality of data you get back often depends on the ability of the interviewer. Also, the size of the sample is limited to the size of your interviewing staff, the area in which the interviews are conducted, and the number of qualified respondents within that area.

Social listening

Social listening is a powerful solution for brands who want to keep an ear to the ground, gathering unfiltered thoughts and opinions from consumers who are posting on social media.

Many social listening tools store data for up to a couple of years, great for trend analysis that needs to compare current and past conversations.

Social listening isn’t limited to text. Images, videos, and emojis often help us better understand what consumers are thinking, saying, and doing better than more traditional research methods.

Perhaps the biggest downside is there are no guarantees with social listening, and you never know what you will (or won’t) find. It can also be tricky to gauge sentiment accurately if the language used is open to misinterpretation, for example if a social media user describes something as “sick”.

There’s also a potential problem around what people say vs. what they actually do. Tweeting about the gym is a good deal easier than actually going. The wider problem – and this may shock you – is that not every single thing people write on social media is necessarily true, which means social listening can easily deliver unreliable results.

Public domain data

Public domain data comes from think tanks and government statistics or research centers like the UK’s National Office for Statistics or the United States Census Bureau and the National Institute of Statistical Sciences. Other sources are things like research journals, news media, and academic material.

Its advantages for market research are it’s cheap (or even free), quick to access, and easily available. Public domain datasets can be huge, so potentially very rich.

On the flip side, the data can be out of date, it certainly isn’t exclusive to you, and the collection methodology can leave much to be desired. But used carefully, public domain data can be a useful source of secondary market research.

Telephone interviews

You know the drill – you get a call from a researcher who asks you questions about a particular topic and wants to hear your opinions. Some even pay or offer other rewards for your time.

Telephone surveys are great for reaching niche groups of consumers within a specific geographic area or connected to a particular brand, or who aren’t very active in online channels. They’re not well-suited for gathering data from broad population groups, simply because of the time and labor involved.

How to use market research

Data isn’t an end in itself; instead it’s a springboard to make other stuff happen. So once you’ve drawn conclusions from your research, it’s time to think of what you’ll actually do based on your findings.

While it’s impossible for us to give a definitive list (every use case is different), here are some suggestions to get you started.

Leverage it . Think about ways to expand the use – and value – of research data and insights, for example by using research to support business goals and functions, like sales, market share or product design.

Integrate it . Expand the value of your research data by integrating it with other data sources, internal and external. Integrating data like this can broaden your perspective and help you draw deeper insights for more confident decision-making.

Justify it . Enlist colleagues from areas that’ll benefit from the insights that research provides – that could be product management, product development, customer service, marketing, sales or many others – and build a business case for using research.

How to choose the right type of market research

Broadly speaking, choosing the right research method depends on knowing the type of data you need to collect. To dig into ideas and opinions, choose qualitative; to do some testing, it’s quantitative you want.

There are also a bunch of practical considerations, not least cost. If a particular approach sounds great but costs the earth then clearly it’s not ideal for any brand on a budget.

Then there’s how you intend to use the actual research, your level of expertise with research data, whether you need access to historical data or just a snapshot of today, and so on.

The point is, different methods suit different situations. When choosing, you’ll want to consider what you want to achieve, what data you’ll need, the pros and cons of each method, the costs of conducting the research, and the cost of analyzing the results.

Market research examples

Independent agency Bright/Shift used GWI consumer insights to shape a high-impact go-to-market strategy for their sustainable furniture client, generating £41K in revenue in the first month. Here’s how they made the magic happen .

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ReviseSociology

A level sociology revision – education, families, research methods, crime and deviance and more!

Seven Examples of Field Experiments for Sociology

Details of the Hawthorne experiment, Rosenthal and Jacobsens’ self-fulfilling prophecy experiment, and the Stanford experiment, and some more contemporary popular examples up to 2014.

Table of Contents

Last Updated on June 12, 2023 by Karl Thompson

Field experiments aren’t the most widely used research method in Sociology, but the examiners seem to love asking questions about them – below are seven examples of this research method.

Looked at collectively, the results of the field experiments below reveal punishingly depressing findings about human action – they suggest that people are racist, sexist, shallow, passive, and prepared to commit violence when ordered to do so by authority figures.

The experiments are outlined in the form of a timeline, with the most recent first providing contemporary examples of field experiments, and those towards the end the more classic examples I’m sure everyone’s has heard of (Rosenthal and Jacobsen for example).

2014 – The Domestic Abuse in the Lift Experiment

A Swedish social experiment recently showed only one person of 53 reacting to what seemed like a scene of domestic abuse in a lift.

Researchers set up a hidden camera in a lift while members of the group played an abusive boyfriend and his victim. The male actors swore at the women and physically assaulted them while members of the public were in the lift

Most of the lift’s passengers ignored the abuse, while only one out of 53 people intervened in an attempt to stop it.

The experiment was organised by STHLM Panda , which describes itself as “doing social experiments, joking with people and documenting the society we live in”.

2010 – The Ethnicity/ Gender and Bike Theft Experiment

In this experiment two young male actors, dressed in a similar manner, one white the other black take it in turns to act out stealing a bike which is chained to a post in a public park. The two actors (one after the other) spend an hour hacksawing/ bolt-cuttering their way through the bike lock (acting this out several times over) as about 100 people walk by in each case.

The findings – when the white actor acts out the bike-theft, only 1/100 step in and take immediate action. Several people actually casually ask ‘is that your bike’, but just laugh it off when the actor tells them it isn’t.

When the black actor acts out the same thing, within seconds, a crowd of people has gathered to stop him, with many whipping out their mobiles to phone the police. When the experiment is reset, the same thing happens again.

Towards the end of the film, a third actor steps in – an attractive young, blonde female – people actually help her to steal the bike!

This experiment seems to have quite good reliability – there are some examples of similar experiments which get similar results…

The ‘Social Misfits’ experiment where a white guy then a black guy act out a car theft on a public road – the white guy lasts 30 mins and ‘no one cares’, but not so with the black-guy.

2009 – The Ethnicity and Job Application Experiment

Researchers sent nearly 3,000 job applications under false identities in an attempt to discover if employers were discriminating against jobseekers with foreign names.

They found that an applicant who appeared to be white would send 9 applications before receiving a positive response of either an invitation to an interview or an encouraging telephone call. Minority candidates with the same qualifications and experience had to send 16 applications before receiving a similar response .

Researchers from the National Centre for Social Research , commissioned by the Department for Work and Pension (DWP), sent three different applications for 987 actual vacancies between November 2008 and May 2009. Using names recognisably from three different communities – Nazia Mahmood, Mariam Namagembe and Alison Taylor – false identities were created with similar experience and qualifications. Every false applicant had British education and work histories. Nine occupations were chosen, ranging from highly qualified positions such as accountants and IT technicians to less well-paid positions such as care workers and sales assistants.

All the job vacancies were in the private, public and voluntary sectors and were based in Birmingham, Bradford, Bristol, Glasgow, Leeds, London and Manchester. The report concludes that there was no plausible explanation for the difference in treatment found between white British and ethnic minority applicants other than racial discrimination .

It also found that public sector employers were less likely to have discriminated on the grounds of race than those in the private sector (a handy argument against privatisation and neoliberalism here, at least if you’re not racist!)

2008 – The £5 Note Theft and Social Disorder Experiment

In this (slightly bizarre sounding) experiment an envelope containing a £5 note was left poking out a letterbox, in such a way that the £5 note was easily visible. The researchers did this first of all with a tidy garden, and later on (similar time of day) with litter in the garden – on the first occasion 13% of people took the envelope, on the second, the percentage doubled to 25% – suggesting that signs of physical disorder such as littering encourage deviant behaviour.

The experiment was actually a bit more complex – for the full details see the Keizer et al source below – this was also actually one of six experiments designed to test out Wilson and Kelling’s 1996 ‘broken windows theory’.

1971 – The Stanford Prison Experiment

In which college students take on the role of either prison guards or prisoners and spend time in an artificial prison. The Stanford Prison Experiment was meant to last 14 days, it had to be stopped after just six because the ‘guards’ became abusive and the ‘prisoners’ began to show signs of extreme stress and

In 1971, psychologist Philip Zimbardo and his colleagues set out to create an experiment that looked at the impact of becoming a prisoner or prison guard. The researchers set up a mock prison in the basement of Standford University’s psychology building, and then selected 24 undergraduate students to play the roles of both prisoners and guards.

The simulated prison included three six by nine foot prison cells. Each cell held three prisoners and included three cots. Other rooms across from the cells were utilized for the prison guards and warden. One very small space was designated as the solitary confinement room, and yet another small room served as the prison yard.

The 24 volunteers were then randomly assigned to either the prisoner group or the guard group. Prisoners were to remain in the mock prison 24-hours a day for the duration of the study. Guards, on the other hand, were assigned to work in three-man teams for eight-hour shifts. After each shift, guards were allowed to return to their homes until their next shift. Researchers were able to observe the behavior of the prisoners and guards using hidden cameras and microphones.

While the prisoners and guards were allowed to interact in any way they wanted, the interactions were generally hostile or even dehumanizing. The guards began to behave in ways that were aggressive and abusive toward the prisoners, while the prisoners became passive and depressed. Five of the prisoners began to experience such severe negative emotions, including crying and acute anxiety, that they had to be released from the study early.

The Stanford Prison Experiment demonstrates the powerful role that the situation can play in human behaviour. Because the guards were placed in a position of power, they began to behave in ways they would not normally act in their everyday lives or in other situations. The prisoners, placed in a situation where they had no real control, became passive and depressed.

1968 – Rosenthal and Jacobson’s ‘Self-Fulfilling Prophecy’ Experiment

The aim of this research was to isolate and measure the effect of high teacher expectation on the educational performance of pupils.

Rosenthal and Jacobson carried out their research in a California primary school they called ‘Oak School’. Pupils were given an IQ test and on the basis of this R and J informed teachers that 20% of the pupils were likely ‘spurt’ academically in the next year. In reality, however, the 20% were randomly selected.

All of the pupils were re-tested 8 months later and he spurters had gained 12 IQ points compared to an average of 8.

Rosenthal and Jacobsen concluded that higher teacher expectations were responsible for this difference in achievement, providing supporting evidence for labelling theory and the ‘self-fulfilling prophecy’.

1924-32 The Hawthorne Factory Experiments

The Hawthorne Electricity Factory Works in Chicago commissioned a study to see if their workers would become more productive in response to various changes in their working environment – such as lighting levels, cleanliness of the factory and relocating work stations.

The workers’ productivity seemed to improve with any changes made, and slumped when the study ended. It was suggested that the productivity gain occurred because the workers were more motivated due to the increased interest being shown in them during the experiments.

The study gave rise to the term ‘The Hawthorne Effect’ which refers to any short-term changes in behaviour which result from participants knowing they are taking part in an experiment (rather than changes in behaviour being a result of changes to independent variables).

NB – As the video outlines, this study was huge – really more than just a ‘field experiment’ it involved the workers being interviewed about their feelings about work.

Field Experiments in Sociology – covers the strengths and limitations of the method

An Introduction to Experiments – covering key terms related to experiments, such as hypotheses, and dependent and independent variables.

Field Experiments are an important research method within sociology.

Swedish social experiment shows people ignoring domestic abuse in a lift – The Guardian

Double standard bike thief experiment highlights racism – The Root

Undercover job hunters reveal huge race bias in Britain’s workplaces – The Guardian

Keizer et al – The Spreading of Disorder – Science Express Report

The Stanford Prison Experiment – The official web site of the experiment (possibly the only experiment that’s also a celebrity?!)

The Pygmalion Effect (details of Rosenthal and Jacobson’s study) – Wikipedia

The Hawthorne Effect – Wikipedia

6 thoughts on “Seven Examples of Field Experiments for Sociology”

Many are but there is overlap between psychology and sociology, there are so few within sociology we have to draw on our sister subject!

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Most of these are psychology, not sociology.

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CRO Guide > Chapter 3.1

Qualitative Research: Definition, Methodology, Limitation & Examples

Qualitative research is a method focused on understanding human behavior and experiences through non-numerical data. Examples of qualitative research include:

One-on-one interviews,
Focus groups, Ethnographic research,
Case studies,
Record keeping,
Qualitative observations

In this article, we’ll provide tips and tricks on how to use qualitative research to better understand your audience through real world examples and improve your ROI. We’ll also learn the difference between qualitative and quantitative data.

Marketers often seek to understand their customers deeply. Qualitative research methods such as face-to-face interviews, focus groups, and qualitative observations can provide valuable insights into your products, your market, and your customers’ opinions and motivations. Understanding these nuances can significantly enhance marketing strategies and overall customer satisfaction.

What is Qualitative Research

Qualitative research is a market research method that focuses on obtaining data through open-ended and conversational communication. This method focuses on the “why” rather than the “what” people think about you. Thus, qualitative research seeks to uncover the underlying motivations, attitudes, and beliefs that drive people’s actions.

Let’s say you have an online shop catering to a general audience. You do a demographic analysis and you find out that most of your customers are male. Naturally, you will want to find out why women are not buying from you. And that’s what qualitative research will help you find out.

In the case of your online shop, qualitative research would involve reaching out to female non-customers through methods such as in-depth interviews or focus groups. These interactions provide a platform for women to express their thoughts, feelings, and concerns regarding your products or brand. Through qualitative analysis, you can uncover valuable insights into factors such as product preferences, user experience, brand perception, and barriers to purchase.

Types of Qualitative Research Methods

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience regarding a particular topic.

The most frequently used qualitative analysis methods are one-on-one interviews, focus groups, ethnographic research, case study research, record keeping, and qualitative observation.

1. One-on-one interviews

Conducting one-on-one interviews is one of the most common qualitative research methods. One of the advantages of this method is that it provides a great opportunity to gather precise data about what people think and their motivations.

Spending time talking to customers not only helps marketers understand who their clients are, but also helps with customer care: clients love hearing from brands. This strengthens the relationship between a brand and its clients and paves the way for customer testimonials.

A company might conduct interviews to understand why a product failed to meet sales expectations.
A researcher might use interviews to gather personal stories about experiences with healthcare.

These interviews can be performed face-to-face or on the phone and usually last between half an hour to over two hours.

When a one-on-one interview is conducted face-to-face, it also gives the marketer the opportunity to read the body language of the respondent and match the responses.

2. Focus groups

Focus groups gather a small number of people to discuss and provide feedback on a particular subject. The ideal size of a focus group is usually between five and eight participants. The size of focus groups should reflect the participants’ familiarity with the topic. For less important topics or when participants have little experience, a group of 10 can be effective. For more critical topics or when participants are more knowledgeable, a smaller group of five to six is preferable for deeper discussions.

The main goal of a focus group is to find answers to the “why”, “what”, and “how” questions. This method is highly effective in exploring people’s feelings and ideas in a social setting, where group dynamics can bring out insights that might not emerge in one-on-one situations.

A focus group could be used to test reactions to a new product concept.
Marketers might use focus groups to see how different demographic groups react to an advertising campaign.

One advantage that focus groups have is that the marketer doesn’t necessarily have to interact with the group in person. Nowadays focus groups can be sent as online qualitative surveys on various devices.

Focus groups are an expensive option compared to the other qualitative research methods, which is why they are typically used to explain complex processes.

3. Ethnographic research

Ethnographic research is the most in-depth observational method that studies individuals in their naturally occurring environment.

This method aims at understanding the cultures, challenges, motivations, and settings that occur.

A study of workplace culture within a tech startup.
Observational research in a remote village to understand local traditions.

Ethnographic research requires the marketer to adapt to the target audiences’ environments (a different organization, a different city, or even a remote location), which is why geographical constraints can be an issue while collecting data.

This type of research can last from a few days to a few years. It’s challenging and time-consuming and solely depends on the expertise of the marketer to be able to analyze, observe, and infer the data.

4. Case study research

The case study method has grown into a valuable qualitative research method. This type of research method is usually used in education or social sciences. It involves a comprehensive examination of a single instance or event, providing detailed insights into complex issues in real-life contexts.

Analyzing a single school’s innovative teaching method.
A detailed study of a patient’s medical treatment over several years.

Case study research may seem difficult to operate, but it’s actually one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

Record keeping is similar to going to the library: you go over books or any other reference material to collect relevant data. This method uses already existing reliable documents and similar sources of information as a data source.

Historical research using old newspapers and letters.
A study on policy changes over the years by examining government records.

This method is useful for constructing a historical context around a research topic or verifying other findings with documented evidence.

6. Qualitative observation

Qualitative observation is a method that uses subjective methodologies to gather systematic information or data. This method deals with the five major sensory organs and their functioning, sight, smell, touch, taste, and hearing.

Sight : Observing the way customers visually interact with product displays in a store to understand their browsing behaviors and preferences.
Smell : Noting reactions of consumers to different scents in a fragrance shop to study the impact of olfactory elements on product preference.
Touch : Watching how individuals interact with different materials in a clothing store to assess the importance of texture in fabric selection.
Taste : Evaluating reactions of participants in a taste test to identify flavor profiles that appeal to different demographic groups.
Hearing : Documenting responses to changes in background music within a retail environment to determine its effect on shopping behavior and mood.

Below we are also providing real-life examples of qualitative research that demonstrate practical applications across various contexts:

Qualitative Research Real World Examples

Let’s explore some examples of how qualitative research can be applied in different contexts.

1. Online grocery shop with a predominantly male audience

Method used: one-on-one interviews.

Let’s go back to one of the previous examples. You have an online grocery shop. By nature, it addresses a general audience, but after you do a demographic analysis you find out that most of your customers are male.

One good method to determine why women are not buying from you is to hold one-on-one interviews with potential customers in the category.

Interviewing a sample of potential female customers should reveal why they don’t find your store appealing. The reasons could range from not stocking enough products for women to perhaps the store’s emphasis on heavy-duty tools and automotive products, for example. These insights can guide adjustments in inventory and marketing strategies.

2. Software company launching a new product

Method used: focus groups.

Focus groups are great for establishing product-market fit.

Let’s assume you are a software company that wants to launch a new product and you hold a focus group with 12 people. Although getting their feedback regarding users’ experience with the product is a good thing, this sample is too small to define how the entire market will react to your product.

So what you can do instead is holding multiple focus groups in 20 different geographic regions. Each region should be hosting a group of 12 for each market segment; you can even segment your audience based on age. This would be a better way to establish credibility in the feedback you receive.

3. Alan Pushkin’s “God’s Choice: The Total World of a Fundamentalist Christian School”

Method used: ethnographic research.

Moving from a fictional example to a real-life one, let’s analyze Alan Peshkin’s 1986 book “God’s Choice: The Total World of a Fundamentalist Christian School”.

Peshkin studied the culture of Bethany Baptist Academy by interviewing the students, parents, teachers, and members of the community alike, and spending eighteen months observing them to provide a comprehensive and in-depth analysis of Christian schooling as an alternative to public education.

The study highlights the school’s unified purpose, rigorous academic environment, and strong community support while also pointing out its lack of cultural diversity and openness to differing viewpoints. These insights are crucial for understanding how such educational settings operate and what they offer to students.

Even after discovering all this, Peshkin still presented the school in a positive light and stated that public schools have much to learn from such schools.

Peshkin’s in-depth research represents a qualitative study that uses observations and unstructured interviews, without any assumptions or hypotheses. He utilizes descriptive or non-quantifiable data on Bethany Baptist Academy specifically, without attempting to generalize the findings to other Christian schools.

4. Understanding buyers’ trends

Method used: record keeping.

Another way marketers can use quality research is to understand buyers’ trends. To do this, marketers need to look at historical data for both their company and their industry and identify where buyers are purchasing items in higher volumes.

For example, electronics distributors know that the holiday season is a peak market for sales while life insurance agents find that spring and summer wedding months are good seasons for targeting new clients.

5. Determining products/services missing from the market

Conducting your own research isn’t always necessary. If there are significant breakthroughs in your industry, you can use industry data and adapt it to your marketing needs.

The influx of hacking and hijacking of cloud-based information has made Internet security a topic of many industry reports lately. A software company could use these reports to better understand the problems its clients are facing.

As a result, the company can provide solutions prospects already know they need.

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Qualitative Research Approaches

Once the marketer has decided that their research questions will provide data that is qualitative in nature, the next step is to choose the appropriate qualitative approach.

The approach chosen will take into account the purpose of the research, the role of the researcher, the data collected, the method of data analysis , and how the results will be presented. The most common approaches include:

Narrative : This method focuses on individual life stories to understand personal experiences and journeys. It examines how people structure their stories and the themes within them to explore human existence. For example, a narrative study might look at cancer survivors to understand their resilience and coping strategies.
Phenomenology : attempts to understand or explain life experiences or phenomena; It aims to reveal the depth of human consciousness and perception, such as by studying the daily lives of those with chronic illnesses.
Grounded theory : investigates the process, action, or interaction with the goal of developing a theory “grounded” in observations and empirical data.
Ethnography : describes and interprets an ethnic, cultural, or social group;
Case study : examines episodic events in a definable framework, develops in-depth analyses of single or multiple cases, and generally explains “how”. An example might be studying a community health program to evaluate its success and impact.

How to Analyze Qualitative Data

Analyzing qualitative data involves interpreting non-numerical data to uncover patterns, themes, and deeper insights. This process is typically more subjective and requires a systematic approach to ensure reliability and validity.

1. Data Collection

Ensure that your data collection methods (e.g., interviews, focus groups, observations) are well-documented and comprehensive. This step is crucial because the quality and depth of the data collected will significantly influence the analysis.

2. Data Preparation

Once collected, the data needs to be organized. Transcribe audio and video recordings, and gather all notes and documents. Ensure that all data is anonymized to protect participant confidentiality where necessary.

3. Familiarization

Immerse yourself in the data by reading through the materials multiple times. This helps you get a general sense of the information and begin identifying patterns or recurring themes.

Develop a coding system to tag data with labels that summarize and account for each piece of information. Codes can be words, phrases, or acronyms that represent how these segments relate to your research questions.

Descriptive Coding : Summarize the primary topic of the data.
In Vivo Coding : Use language and terms used by the participants themselves.
Process Coding : Use gerunds (“-ing” words) to label the processes at play.
Emotion Coding : Identify and record the emotions conveyed or experienced.

5. Thematic Development

Group codes into themes that represent larger patterns in the data. These themes should relate directly to the research questions and form a coherent narrative about the findings.

6. Interpreting the Data

Interpret the data by constructing a logical narrative. This involves piecing together the themes to explain larger insights about the data. Link the results back to your research objectives and existing literature to bolster your interpretations.

7. Validation

Check the reliability and validity of your findings by reviewing if the interpretations are supported by the data. This may involve revisiting the data multiple times or discussing the findings with colleagues or participants for validation.

8. Reporting

Finally, present the findings in a clear and organized manner. Use direct quotes and detailed descriptions to illustrate the themes and insights. The report should communicate the narrative you’ve built from your data, clearly linking your findings to your research questions.

Limitations of qualitative research

The disadvantages of qualitative research are quite unique. The techniques of the data collector and their own unique observations can alter the information in subtle ways. That being said, these are the qualitative research’s limitations:

1. It’s a time-consuming process

The main drawback of qualitative study is that the process is time-consuming. Another problem is that the interpretations are limited. Personal experience and knowledge influence observations and conclusions.

Thus, qualitative research might take several weeks or months. Also, since this process delves into personal interaction for data collection, discussions often tend to deviate from the main issue to be studied.

2. You can’t verify the results of qualitative research

Because qualitative research is open-ended, participants have more control over the content of the data collected. So the marketer is not able to verify the results objectively against the scenarios stated by the respondents. For example, in a focus group discussing a new product, participants might express their feelings about the design and functionality. However, these opinions are influenced by individual tastes and experiences, making it difficult to ascertain a universally applicable conclusion from these discussions.

3. It’s a labor-intensive approach

Qualitative research requires a labor-intensive analysis process such as categorization, recording, etc. Similarly, qualitative research requires well-experienced marketers to obtain the needed data from a group of respondents.

4. It’s difficult to investigate causality

Qualitative research requires thoughtful planning to ensure the obtained results are accurate. There is no way to analyze qualitative data mathematically. This type of research is based more on opinion and judgment rather than results. Because all qualitative studies are unique they are difficult to replicate.

5. Qualitative research is not statistically representative

Because qualitative research is a perspective-based method of research, the responses given are not measured.

Comparisons can be made and this can lead toward duplication, but for the most part, quantitative data is required for circumstances that need statistical representation and that is not part of the qualitative research process.

While doing a qualitative study, it’s important to cross-reference the data obtained with the quantitative data. By continuously surveying prospects and customers marketers can build a stronger database of useful information.

Quantitative vs. Qualitative Research

Qualitative and quantitative research side by side in a table

Image source

Quantitative and qualitative research are two distinct methodologies used in the field of market research, each offering unique insights and approaches to understanding consumer behavior and preferences.

As we already defined, qualitative analysis seeks to explore the deeper meanings, perceptions, and motivations behind human behavior through non-numerical data. On the other hand, quantitative research focuses on collecting and analyzing numerical data to identify patterns, trends, and statistical relationships.

Let’s explore their key differences:

Nature of Data:

Quantitative research : Involves numerical data that can be measured and analyzed statistically.
Qualitative research : Focuses on non-numerical data, such as words, images, and observations, to capture subjective experiences and meanings.

Research Questions:

Quantitative research : Typically addresses questions related to “how many,” “how much,” or “to what extent,” aiming to quantify relationships and patterns.
Qualitative research: Explores questions related to “why” and “how,” aiming to understand the underlying motivations, beliefs, and perceptions of individuals.

Data Collection Methods:

Quantitative research : Relies on structured surveys, experiments, or observations with predefined variables and measures.
Qualitative research : Utilizes open-ended interviews, focus groups, participant observations, and textual analysis to gather rich, contextually nuanced data.

Analysis Techniques:

Quantitative research: Involves statistical analysis to identify correlations, associations, or differences between variables.
Qualitative research: Employs thematic analysis, coding, and interpretation to uncover patterns, themes, and insights within qualitative data.

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Quantitative Methods in Sociological Research by Erin Leahey LAST REVIEWED: 27 July 2011 LAST MODIFIED: 27 July 2011 DOI: 10.1093/obo/9780199756384-0044

Principles of Sociological Inquiry – Qualitative and Quantitative Methods

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Soc 156: Quantitative Methods in Sociology

2.2 Research Methods

Field Research

Sociology in the Real World

Participant Observation

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Institutional Ethnography

Sociological Research

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Secondary Data Analysis

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Definition of Quantitative Research

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Qualitative vs Quantitative Research

Common Research Methods

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Research Methods: Quantitative and Qualitative Methods

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