research design and methodology ppt

Guide to Research Methods

About the guide

This guide will

• Introduce you to a range of research methods
• Help you think about the value and limitations of different research methods
• Identify when to use alternative research methods

You should use the guide

• After or while you establish your research questions (See the Guide to Research Questions )
• When you are completing your Research Design Framework
• When you are thinking about who you want to talk to and why (See the Guide to Sampling )

You should print or read this guide

These slides are set up so that they can be printed back to back (two/four sided) to give:

• A short hand overview about when to use each method
• A summary of the method, what it’s good for and limitations (linking to other slides in this pack)

Choosing research methods

When you need to think about which method is best in theory and in practice

Choosing Research Methods

Providing a rationale for the methods you choose to use and how you employ them.

• What are your research goals? If you are looking to influence experts or policy makers, quantitative approaches will add weight to your findings. If you are looking to understand problems, inform innovation or develop a prototype, look at qualitative methods or user research
• What are your research questions? If they begin with ‘explore’ or ‘what’ look at qualitative methods (talking). If they begin with ‘identify’ or ‘why’ look at quantitative (see guide to research questions )
• What research traditions exist? You may choose to follow or challenge them. Think about whether you want your research to be noted for its quality and robustness or creative approach and unique insights
• What are your/your teams skills? You may not be an expert in the most appropriate method so consider asking for other team members or commissioning out research
• Who are you research participants? Think about your relationship to participants (especially if you are doing qualitative research) and how they will respond to you and the method. Consider if they are often consulted or surveyed and whether if could be helpful or unhelpful to stick with their comfort zone or not.

Using online tools

When you need to decide which tools to use for research

What to think about when choosing a tool to conduct research

• What’s the cost to the research quality ? Most tools are ‘freemium’, use a basic version for free. BUT these are designed to annoy you to pay to do good research. Consider privacy settings, data access, storage and value for money. Survey tools will have no option to filter participants (if yes/no answer this q), a 10Q limit, no branding. Mapping/visualisations are published online and open source tools aren’t always user friendly
• Start with user needs, understand the context and think about everyone. Consider what technology they have, how they will access the tool and what they need to do this. Do they have internet, data, time?
• Be creative: Online tools may not be designed for research, but Google Forms, Trello, Workflowy and Slack are all valuable collaboration tools. Twitter and Facebook polls may increase participation in research. However, think about what they are missing, what they can’t do and pilot your analysis approach first
• See what’s out there: This online sheet of Applied Social Research Guides and Resources includes a list of online tools for research and evaluation to test. Those widely used for your research method or sector are likely to be the best starting point. Some tools allow you to do research (see Tags for Twitter data capture), analyse it or present it in new ways (see Raw Graph s for data visualisation)

Contents: Methods summary

• Structured Interviews : When you want to gain a broad range of perspectives about specific questions
• Semi-Structured Interviews : When you want to gain in-depth insights about broad questions
• Unstructured Interviews : When you want to gain in-depth insights about a complex research topics
• Telephone Interviews : A tool for when you want to interview people quickly and easily
• Guerilla Interviews : When you want to carry out user research or explore general perspectives quickly
• Contextual Interviews : When you want to understand actions and particular experiences indepth and in context
• Focus Groups : When you want to understand shared experiences and different perspectives
• Participant Observation : When you want to ‘learn by doing’ or observe social interactions and behaviour
• Ethnography : When you want to experience social practices, interactions and behaviour with minimal influence
• Surveys: When you want to generate numerical data about the scale of people’s opinions and feelings
• Mixed Methods: When one method cannot fully answer your main research question
• User Research : When you want to learn about the behaviours and motivations of your target audience
• Service Design Research : When you want to design a service to meet people’s needs.
• Content Analysis : When you want to understand public discourse through secondary or online data
• Workshops : When you want to engage stakeholders in research, generate ideas or codesign solutions
• Usability tests : When you want to test prototypes or learn about problems with an existing service

Find out more

How to do good…

• Applied social research: A curated online sheet of Applied Social Research Guides and Resources
• Surveys : Guide to creating questions here and here , build on existing data/questions , analysis guide
• Interviews : A nice overview here which includes how to structure an interview
• User research : The GDS for intro guides and DisAmbiguity blog
• Service design: This is Service Design Doing has great tools and formats for workshops

Inspiration for emerging research methods and creative formats for research

• Ethnography and mixed methods presented well: Ikea At Home Report
• User mapping techniques as a social research method NPC Report
• User Research to understand domestic abuse experiences and the potential for technology Tech Vs Abuse
• Using Twitter data for social research Demos
• Data visualisation as a tool for research communication - Nesta data visualisation and Women’s Aid Map
• Data journalism and data storytelling - Guardian reading the riots
• An online games to shift perspective on a social problem - Financial Times Uber Story
• Content analysis to map trends - Nesta analysed creative skills in job adverts
• Issue mapping online - networks of websites and people on Twitter - Warwick University Issue Mapping

Structured Interviews

When you want to gain a broad range of perspectives about specific questions

Also consider

Semi-structured interviews

A conversation with a set structure (a script of fixed questions) and specific purpose. Can be a method to undertake a survey or called a ‘directed’ interview.

• Asking standardised questions across many participants makes data easier to analyse and compare
• Giving participants a clear guide about what you want to learn from them
• Topics that would be too complex to capture in a questionnaire tick box/short response
• Respondents with limited time, who want to consider responses in advance or do not want to write
• The quality of the interview is less dependent on the interviewer and their rapport with the interviewee

Limitations (and how to avoid or what to consider instead)

• The structure prevents participants from bringing in other ideas (consider semi-structured interviews )
• Whilst quicker to conduct and analyse than semi-structured interviews, they are still resource intensive and only possible to do with limited numbers of people (consider questionnaires online - see surveys )

Semi-Structured Interviews

When you want to gain in-depth insights about broad questions

Participant Observation

User research

Focus groups

Semi-Structured interviews

Conversation with a structure (set of open questions) and clear purpose. Also called directed interviews.

• Exploring a range of perspectives on research questions, engaging experts and getting buy-in to research
• Gaining in-depth insights about how people feel or interpret complex issues
• Topics which are sensitive, difficult to express in writing or to articulate views about in a survey
• Allowing participants to respond in their words, framing what they see as important

Limitations

• Quality can depend on interviewer skills and put people on the spot (consider setting topics in advance)
• The set-up affects the quality of engagement and discussion (consider location, relationship with the interviewee and whether you should do a face to face or Telephone/Online interview )
• Time consuming to do, analyse and compare (consider Structured Interviews or Focus groups )
• Can lack validity as evidence (consider Surveys )
• Explore what people say, think and remember, not what they actually do (consider Participant Observation contextual interviews or User Research ) or shared perspectives (consider Focus groups )
• Easy to provide too much structure and prevent open exploration of a topic (see unstructured interviews )

Unstructured Interviews

When you want to gain in-depth insights about a complex research topics

Contextual interviews

Unstructured interviews

A loosely structured open conversation guided by research topics (also called non-directed interviews)

• Very exploratory research and broad research questions
• Letting the participant guide the interview according to their priorities and views
• In-depth and broad discussion about a person's expertise, experiences and opinions
• Participant can feel like the they are not saying the ‘right’ thing (explain technique and rationale well)
• Whilst useful for expert interviews, an unstructured approach can give the impression that the interviewer is unprepared, lacks knowledge or the research purpose is unclear (consider semi-structured interviews )
• Interviews are longer, resource intensive and only smaller numbers are possible (consider focus groups )
• Generates in-depth insights that are difficult to analyse and compare
• A lack of structure can encourage participants to focus in-depth on one thing they are positive about or know very well in-depth (consider using desk research to inform the interview topics)

Guerilla Interviews

When you want to carry out user research or explore general perspectives quickly and easily

An ‘impromptu’ approach to interviewing, often talking to real people on the street or at a key site

• Gaining immediate responses to a tool or design and insights into a problem
• Informal method means participants can be more relaxed and open
• Speaking to a lot of people, simply, quickly and cheaply about one key question
• User research and user experience of interacting with digital products
• Speaking to people for convenience (users are available in a single place and time) introduces sample bias (but you can add more targeting and profiling of participants, see the Guide to Sampling )
• The lack of formal structure can mean that you miss important questions or insights
• Findings are often unreliable and not generalisable because they rely on a single type of user
• Difficult to understand complexity or gain contextual insights

Telephone / online interviews

A tool for when you want to interview people quickly and easily

Telephone or Online interviews

A tool to conduct an interview (it is not a method in itself) which is not in person/ face to face

• Conducting interviews without the costs of travel and meeting time (often shorter)
• Expert and stakeholder interviews, when you already know the participant well or they are short of time
• Taking notes and looking up information whilst interviewing is less disruptive than in person, easy to record
• Sending informed consent information and interview questions in advance
• Can be difficult to undertake an engaging interview (hard to build rapport on the phone)
• Often need to be shorter and put alongside other meetings

What method are you using?

• Structured interviews : When you want to gain a broad range of perspectives about specific questions
• Semi-structured interviews : When you want to gain in-depth insights about broad questions
• Unstructured interviews : When you want to gain in-depth insights about a complex research topics

Further guides to Interviews : A nice overview here , including how to structure an interview

Contextual Interview

When you want to understand actions and particular experiences in-depth and in context

Ethnography

Interviews conducted with people in a situational context relevant to the research question; also known as contextual inquiry.

• Understanding what happens, experiences and emotions whilst interacting with a tool, service or event.
• Easier for research participants to show rather than explain, participants are active and engaged
• Uncover what happens, what people do, how they behave in the moment, rather than how they remember this and give meaning to these responses later.
• Open and flexible method giving depth of insights about a tool or specific interaction
• Time and resource intensive for the researcher
• Each context is unique - making it difficult to generalise from or to answer broader research questions about experiences (consider semi-structured interviews )
• The researcher influences the interactions and events (consider ethnography or participant observation )

When you want to understand shared experiences and different perspectives

Focus Groups

An organised discussion with a group of participants, led by a facilitator around a few key topics

• Gaining several perspectives about the same topic quickly
• Research contexts and topics where familiarity between participants can generate discussion about similar experiences (or different ones) which may not arise in a one to one interview
• When attitudes, feelings and beliefs are more likely to be revealed in social gathering and interactions
• Including tasks and creative methods to elicit views (e.g. shared ranking of importance of statements)
• Difficult to identify the individual view from the group view (consider semi-structured interviews )
• Group dynamics will affect the conversation focus and participation levels of different members
• The role of the moderator is very significant. Good levels of group leadership and interpersonal skill are required to moderate a group successfully.
• The group set-up is an ‘artificial’ social setting and discussion (consider Participant Observation )

Participant observation

When you want to ‘learn by doing’ and observe social interactions and behaviour

Participant observation/ shadowing

The researcher immerses themselves in lives of participants as an ‘observer’ of their behaviours, practices and interactions. A type of ethnography. The people being observed know about the research.

• Understanding everyday behaviours, interactions and practice in the context that they occur
• Gaining an intuitive understanding of what happens in practice and what this means for those involved
• Allowing research participants to show you what they do, when they can’t describe and remember this well
• Establishing topics for further investigation through more structured or focused research methods
• If explicit (shadowing for example) the research situation is still ‘artificial’
• Your audience may not respect it and can be difficult to generalise from (consider mixed methods)
• The quality of the data is dependent on the researchers’ skills and relationships with participants

When you want to experience social practices, interactions and behaviour with minimal influence on what happens

The systematic study of a group of people or cultures to understand behaviours and interactions. The researcher becomes an ‘insider’. It is a way of presenting research findings, as well as a method, which can include participant observation, document analysis and visual methods.

• When you need to be an ‘insider’ to fully access the research context (such as organisational cultures)
• Presenting how everyday behaviours, interactions and practice occur in context
• Gaining an in-depth knowledge of your research context, participants and social relationships
• When little is known about a research context or topic
• If covert (at a conference or workplace for example) it has implications for informed consent
• If explicit (shadowing for example) the researcher’s presence can affect the interactions and findings

Example use case : Ikea At Home research study to understand how people feel about their home

When you want to generate numerical data about the scale of people’s opinions and feelings

Mixed Methods

A process of systematically collecting information from a large number of different people. Responses are summarised as statistics (online surveys automate this analysis for you).

• Targeting specific types of research participant and providing data about their views
• If designed well, they can be quick, simple and non intrusive for research participants
• Findings can have more credibility than other methods because of their breadth
• Describing, measuring and understanding (a basic questionnaire)
• Statistical analysis, modelling cause and effect (large scale survey designed to represent the population)
• Can raise more questions about what happens and why, lack depth of insight (consider mixed methods )
• Hard to design well and require a lot of time upfront and data skills to analyse the results
• Low completion rates and people feel ‘over surveyed’ (consider incentives )
• Assumes people will be honest and sufficiently aware of the research context to provide credible answers.

Further information: A great guide to creating questions here and here , build on existing data/questions here

When one research method cannot fully answer your main research question

Mixed methods

Combining different methods to answer your research questions, can be a mix of quantitative or qualitative methods or both. It may mean working with different types of data, research designs or being part of a research team (covering different research disciplines)

• Overcoming the limitation of relying on a single research method or approach
• Triangulating findings (i.e. using an additional method) can give them more validity
• Accessing different types of research participants
• A more holistic understanding about how, why and the extent to which something happens
• Answering different types of research questions about frequency and perceptions
• Giving findings more validity and influence because of the range of data and insights
• Requires a broader range of skills and more time to deliver, analyse and report on
• Research design must have strong sequencing (when each method is used and analysed , why) to make the most of a mixed methods approach - not always possible in a tight timescale or short research project

User Research

When you want to learn about people’s needs, behaviours and motivations for using a service

Service Design

S emi-Structured Interviews

Usability testing

A research approach employed to understand users and their needs, motivations and behaviours, primarily to inform service design.

• User-centered design processes which look to ensure services meet the needs of their audience
• Gaining specific insights into how a person interacts with a digital tool or service
• Exploring general needs, behaviours and motivations for a specific target group using a range of services
• Focus on a tool or service can prevent wider analysis, relevance and applicability
• Research can lack credibility due to small numbers, set up, documentation (often highly specific focus)
• Can overlook those who do not use a service for a whole range of reasons

What method?

• User research involves any method which looks at who users are, the problems they face, what they are trying to do and how they use existing services. This can create user personas, user journeys and user experience maps. It largely includes qualitative research methods.

When you want to design a service to meet people’s needs, including planning, organising, infrastructure, communication and components)

A research approach employed in the activity of planning and organising of people, infrastructure, communication and material components of a service, in order to improve quality and interaction.

• Gaining a holistic picture of all components (infrastructure, people, organisations, culture) affecting how a person interacts with a service
• Service design often begins with user research but participants in research include all those involved in delivering (not just using) a service, such as employees and stakeholders in an organisation as well as looking at the context and system which affect how a service works and its effectiveness

Content analysis

When you want to understand public discourse through secondary or online data

A systematic process of classifying and interpreting documents, text or images to analyse key discourses (their meaning) or to quantify patterns (such as word frequencies). This can be done manually or it can be automated.

• Exploring the focus of messages, text or imagery and change over time
• Secondary data sources, such as archives, online social media data (such as Tweets) and news articles
• Gaining a qualitative or quantitative insights about key messages
• Focuses on public and documented interpretations of events and experiences
• Documents are not exhaustive and not all are accessible (or available online/freely)
• Qualitative coding is time intensive to manually classify, reliant on researcher interpretation
• Automated coding for key words can miss nuances and difficult to produce meaningful findings

When you want to engage stakeholders in research, generate ideas or codesign solutions

Also consider:

A tool to undertake research. It is an interactive session, often taking a full day, in which research participants sor stakeholders work intensively on an issue or question. The process can combine elements of qualitative research, brainstorming or problem solving.

• Engaging stakeholders - building empathy with and understanding of research findings
• Understanding problems or prototyping solutions, linked to user research and service design approaches
• Participatory research, allowing participants to shape agendas and outcomes
• Creative, collaborative and engaging activities to build rapport and understanding with participants
• Participatory design, enabling participants to co-design solutions which work for them
• Highly dependent on the right people attending and the facilitation skills
• Can be a lot of time and effort to coordinate a workshop effectively and analyse findings
• The immersive and collaborative environment makes it difficult to document effectively
• Collaborative solutions may duplicate existing problems or solutions

When you want to test prototypes or learn about problems with an existing service

A user research method where you watch participants try to complete specific tasks using your service. Moderated testing involve interaction with the research participant, asking them to explain what they are doing, thinking and feeling. Unmoderated testing is completed alone by the participant.

• Identify any usability issues with a digital service - for example, problems with the language or layout
• Seeing if users understand what they need to do in order to complete designated tasks
• Generating ideas to improve a prototype of existing digital service
• Assessing user experience
• Focus is not on ‘natural’ use (consider contextual interviews , participant observation , ethnography )
• Data is about a specific design and interaction with a tool at that moment
• Findings cannot be generalised or applicable more broadly to understand users and behaviours

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Lecture Notes on Research Methodology

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Introduction to Research Methodology

Sabine Mendes Lima Moura Issues in Research Methodology PUC – November 2014.

Today Concepts underlying inferential statistics

Richard M. Jacobs, OSA, Ph.D.

Research Methodology Lecture 1.

Chapter 12 Inferential Statistics Gay, Mills, and Airasian

Sample Design.

Copyright © 2008 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved. John W. Creswell Educational Research: Planning,

Magister of Electrical Engineering Udayana University September 2011

Chapter 1: Introduction to Statistics

RESEARCH A systematic quest for undiscovered truth A way of thinking

Research Methodology.

Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.

Research Seminars in IT in Education (MIT6003) Quantitative Educational Research Design 2 Dr Jacky Pow.

PROCESSING OF DATA The collected data in research is processed and analyzed to come to some conclusions or to verify the hypothesis made. Processing of.

Academic Research Academic Research Dr Kishor Bhanushali M

Question paper 1997.

Chapter 6: Analyzing and Interpreting Quantitative Data

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Chapter 7 Measuring of data Reliability of measuring instruments The reliability* of instrument is the consistency with which it measures the target attribute.

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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McCombes, S. (2023, November 20). What Is a Research Design | Types, Guide & Examples. Scribbr. Retrieved June 9, 2024, from https://www.scribbr.com/methodology/research-design/

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