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DESCRIPTIVE RESEARCH

Descriptive research to behold is to look beyond the fact; to observe, to go beyond the observation look at the world of people, and you will be overwhelmed by what ... – powerpoint ppt presentation.

To behold is to look beyond the fact to observe, to go beyond the observation
Look at the world of people, and you will be overwhelmed by what you see
But select from that mass of humanity a well-chosen few, and observe them with insight, and they will tell you more than all the multitudes together
Involves either identifying the characteristics of an observed phenomenon or exploring possible correlations among two or more phenomena
In every case, descriptive research examines a situation AS IT IS
It does not involve changing or modifying the situation under investigation, nor is it intended to determine cause-and-effect relationships
Strategies include sampling, making observations, interviewing take on a very different form when we want them to yield quantitative data
Include observation studies, correlational research, developmental designs, and survey research
All of these approaches yield quantitative information that can be summarized through statistical analyses
Survey research is the most frequently used in all disciplines
In qualitative studies, observations are usually recorded in great detail, perhaps with fieldnotes or videotapes that capture the wide variety of ways in which people act and interact
From these data, the researcher constructs a complex yet integrated picture of how people spend their time
In quantitative research, an observation study is quite different
Typically, the focus is on a particular aspect of behaviour
Furthermore, the behaviour is quantified in some way
In some situations, each occurrence of the behaviour is counted to determine its overall frequency
In other situations, the behaviour is rated for accuracy, intensity, maturity, or some other dimension
But regardless of approach, the researcher strives to be as objective as possible in assessing the behaviour being studied
To maintain such objectivity, he or she is likely to use strategies such as the following
1) Define the behaviour being studied in a precise, concrete manner so that the behaviour is easily recognised when it occurs
2) Divide the observation period into small segments and then record whether the behaviour does or does not occur during each segment
3) Use a rating scale to evaluate the behaviour in terms of specific dimensions
4) Have two or three people rate the same behaviour independently, without knowledge of one anothers ratings
5) Train the rater(s) to follow specific criteria when counting or evaluating the behaviour, and continue training until consistent ratings are obtained for any single occurrence of the behaviour
Despite the extensive investment (time and energy), an observational study can yield data that portray much of the richness and complexity of human behaviour
In some situations, then, it provides a quantitative alternative to such approaches as ethnographies and grounded theory studies
A correlational study examines the extent to which differences in one characteristic or variable are related to differences in one or more other characteristics or variables
A correlation exists if, when one variable increases, another variable either increases or decreases in a somewhat predictable fashion
Simple correlation researchers gather data about two or more characteristics numbers that reflect specific measurements of the characteristics in question test scores, CGPAs, ratings,
Each has two numbers, used to calculate correlation coefficient (r)
If perfectly correlated r 1.00 or r -1.00
If unrelated or remotely related, r is close to 0
Moderate correlations are common
Examining only two variables helpful to plot on scatterplot (also known as scattergram) to allow a visual inspection of the relationship between the two variables
Refer to page 181 of the textbook for the scatterplot
The diagonal line running through the middle of the dots is called the line of regression reflects a hypothetical perfect correlation
If all the dots fell exactly on this line, r would be 1.00, dots below the line show children whose reading level is advanced for their age, and dots above the line show children who are lagging a bit in reading
Can make 3 statements from the scatterplot.
1) Can describe the homogeneity or heterogeneity of the two variables (the extent to which the children are similar to or different from one another with respect to age and reading level. Eg. group of only age 6 and 7 has greater homogeneity than group of age 6 - 13)
2) Can describe the degree to which the two variables are intercorrelated by computing the correlation coefficient r
3) The most important, we can interpret the data and give them meaning childrens reading level improves as they grow older, without hesitation as shown by the upward trend of the dots from left to right
In all correlational studies, be alert for faulty logic
Correlation does not, in and of itself, indicate causation
Although in some cases, influence may indeed be present, for example, chronological age influences mental development, including their reading ability
But ultimately we can never infer a cause-and-effect relationship on the basis of correlation alone
One variable correlates meaningfully with another only when a common causal bond links the phenomena of both variables in a logical relationship
Increase in the population of birds in Tasik Serdang has no meaningful relationship with the increase of the population of elephants in Thailand the correlation is simply a fluke and meaningless
In the example, the faulty logic is readily apparent, yet we often see similarly faulty reasoning proposed in correlational research reports
Imagine that a researcher finds a correlation between socioeconomic level and academic performance - it would be all too easy to draw the conclusion that socioeconomic status directly affects academic achievement also if we could improve the familys economic status, then the learning ability of the familys children would also improve
No, no, no! We cannot make an inference about causation on the basis of correlated data alone
It is possible that salary does have an impact on childrens grades, BUT it is equally possible that it does not
May be an undetermined third variable influences BOTH the salary and the childrens school performance
If we were to infer that socioeconomic status directly affects academic achievement, not only would we be going far beyond the data we have, but we would also have trouble accounting for all of the worlds geniuses and intellectual giants, some of whom have been born of indigent parents and grown up in poverty
The data may not lie, but the causal conclusions we draw from the data may, at times, be extremely suspect
Nevertheless, a good researcher must not be content to stop at the point of finding a correlational relationship, because beneath the correlation lie some potentially quite interesting data whose interpretation may conceivably lead to the discovery of new and exciting information
r is just a signpost pointing to further findings
The forces of the correlated data will determine the ultimate meaning of the correlation
We will not find correlation if the measurement instruments have poor validity and reliability
For example, if the reading test used is neither a valid (accurate) nor reliable (consistent) measure of reading achievement, therefore we will not find correlation
To study how a particular characteristic changes, use either 1) a cross-sectional (X-S) study or 2) a longitudinal (LG) study
In a cross-sectional study, a developmental psychologist might study the nature of friendships for children at ages 4, 8, 12, and 16. A gerontologist might consider how retired people in their 70s, 80s, and 90s, are most likely to spend their leisure time
In a longitudinal study, a single group of people is followed over the course of several months or years, and data related to the characteristic(s) under investigation are collected at various times
For example, an educational psychologist might get measures of academic achievement and social adjustment for a group of Year Four students and then, 10 years later, find out which students had completed high school and which ones had not
Obviously, cross-sectional studies are easier to conduct than longitudinal studies, because the researcher can collect all the needed data at a single time, and dont have to worry tracking down people
An additional disadvantage of a longitudinal design is that when people respond repeatedly to the same measurement instrument, they are likely to improve simply because of their practice with the instrument, even if the characteristic being measured hasnt changed at all
A disadvantage of cross-sectional designs is that the different age groups sampled may have been raised under different environmental conditions
Groups of 20-year-olds and 70-year-olds different education standards
A second disadvantage of a cross-sectional design is that we cannot compute correlations between characteristics at different age levels
Survey means to look or see over or beyond
Looking or seeing is not restricted to perception through the physical eye only
Survey research involves acquiring information about one or more groups of people perhaps about their characteristics, opinions, attitudes, or previous experiences by asking them questions and tabulating their answers
The ultimate goal is to learn about a large population by surveying a sample of that population
This approach is called a descriptive survey or normative survey
Reduced to its basic elements, a survey is quite simple in design The researcher poses a series of questions to willing participants summarises their responses with percentages, frequency counts, or more sophisticated statistical indexes and then draws inferences about a particular population from the responses of the sample
It is a common approach, used with more or less sophistication in many areas of human activity
This is not to suggest, however, that because of its frequent use, a survey is any less demanding in its design requirements or any easier for the researcher to conduct than any other type of research
Quite the contrary, the survey design makes critical demands on the researcher that, if not carefully respected, may place the entire research effort in jeopardy
Survey research captures a fleeting moment in time
By drawing conclusions from one transitory collection of data, we may extrapolate about the state of affairs over a longer time period
At best, the extrapolation is a conjecture, and sometimes a hazardous one at that, but it is our only way to generalise from what we see
So often, survey reports that we read seem to suggest that what the researcher found in one sample population at one particular time can be accepted for all time as a constant
An additional consideration in survey research is that we are relying on self-report data
People are telling us what they believe to be true or, perhaps, what they think we want to hear
Peoples memories for events are often distortions of reality What they think happened isnt always what did happen
Furthermore, peoples descriptions of their attitudes and opinions are often constructed on the spot often times, they havent really thought about certain issues until a researcher poses a question about them and so may be coloured by recent events or the current context
An additional problem is that some people may intentionally misrepresent the facts (at least, the facts as they know them) in order to present a favourable impression to the researcher
Survey research typically employs a face-to-face interview, a telephone interview, or a written questionnaire
In survey research, interviews are fairly structured
In a structured interview, the researcher asks a standard set of questions and nothing more
In a semi-structured interview, the research may follow the standard questions with one or more individually tailored questions to get clarification or probe a persons reasoning
The interview tends to be informal and friendly in a qualitative study but more formal and emotionally neutral in a quantitative one
Participants in a qualitative interview may feel as if theyre simply engaging in a friendly chat with the researcher, who is typically someone theyve come to know and trust
In contrast, participants in survey research are continually aware that, yes, this is an interview, and that the temporary relationship theyve formed with the researcher will end once the interview is complete
This is not to say, however, that a survey researcher shouldnt strive to establish rapport with participants
Quite the contrary, the researcher is more likely to gain participants cooperation and encourage them to respond honestly if he or she is likable and friendly and shows a genuine interest in what they have to say
Face-to-face interviews have the distinct advantage of enabling the researcher to establish rapport with potential participants and therefore gain their cooperation thus, such interviews yield the highest response rates the percentages of people agreeing to participate in survey research
However, the time and expense involved may be prohibitive if the needed interviewees reside in a variety of states and countries
Telephone interviews are less time-consuming and less expensive (they involve only the cost of long-distance calls), and the researcher has ready access to virtually anyone on the planet who has a telephone
Although the response rate is not as high as for a face-to-face interview (many people are apt to be busy, annoyed at being bothered, or otherwise not interested in participating), it is considerably higher than for a mailed questionnaire
The researcher cannot establish the same kind of rapport that is possible in a face-to-face situation, and the sample will be biased to the extent that people without phones are part of the population about whom the researcher wants to draw inferences
Personal interviews, whether they be face-to-face or over the telephone, allow the researcher to clarify ambiguous answers and, when appropriate, seek follow-up information
Because such interviews take time, however, they may not be practical when large sample sizes are important
Data lie deep within the minds or attitudes, feelings, or reaction of men/women
Instrument for observing the data beyond the physical reach is the questionnaires since paper-pencil questionnaires can be sent to a large number of people, including those who live thousands of miles away
Thus, they may save the researcher travel expenses, and postage is typically cheaper than a lengthy long-distance telephone call
The social scientist who collects data with a questionnaire and the physicist who determines the presence of radioactivity with a Geiger counter are at just about the same degree of remoteness from their respective sources of data Neither sees the source from which the data originate
The Geiger counter and questionnaires are impersonal probe
They are governed by practical guidelines
From the perspective of survey participants, this distance becomes an additional advantage Participants can respond to questions with assurance that their responses will be anonymous, and so they may be more truthful than they would be in a personal interview, particularly when they are talking about sensitive or controversial issues
Yet questionnaires have their drawbacks as well
Typically, the majority of people who receive questionnaires dont return them in other words, there may be a low return rate and the people who do return them are not necessarily representative of the originally selected sample
Even when people are willing participants in a questionnaire study, their responses will reflect their reading and writing skills and, perhaps, their misinterpretation of one or more questions
Furthermore, by specifying in advance all of the questions that will be asked and thereby eliminating other questions that could be asked about the issue or phenomenon in question the researcher is apt to gain only limited, and possibly distorted, information
Observation studies look at peoples behaviours, and developmental studies, correlational studies, and survey research frequently use questionnaires to learn about peoples behaviours, characteristics, attitudes, and opinions
Behaviours and attitudes are often quite complex and so not, at least on the surface, easily evaluated or quantified
Two techniques that facilitate both evaluation and quantification in such circumstances are the checklist and the rating scale
A checklist is a list of behaviours, characteristics, or other entities that a researcher is investigating. Either the researcher or participants (depending on the study) simply check(s) whether each item on the list is observed, present, or true or else not observed, present, or true
A rating scale is more useful when a behaviour, attitude, or other phenomenon of interest needs to be evaluated on a continuum of, say, inadequate to excellent, never to always, or strongly disapprove to strongly approve
Rating scales were developed by Rensis Likert in the 1930s to assess peoples attitudes accordingly, they are sometimes called Likert scales
Experts have mixed views about letting respondents remain neutral in interviews and questionnaires
If you use rating scales in your own research, you should consider the implications of letting your respondentsstraddle the fence by including a no opinion or other neutral response, and design your scales accordingly
Whenever you use checklists or rating scales, you simplify and more easily quantify peoples behaviours and attitudes
In the process, however, you may lose valuable information
Ultimately you will have to determine whether the trade-offs is worth it for the particular research problem you are investigating
Interviewing involves much more than just asking questions
The questions for the interview should be carefully planned and precisely worded to yield the kinds of data the researcher needs to answer his or her research question
Make sure your interviewees are representative of the group
Find a suitable location
Get written permission
Establish and maintain rapport
Focus on the actual rather than on the abstract or hypothetical
Dont put words in peoples mouths
Record responses verbatim
Keep your reactions to yourself
Remember that you are not necessarily getting the facts
But interviews are typically more structured in quantitative studies than they are in qualitative studies. The following are additional guidelines for conducting interviews in quantitative research
10. As you write the questions, consider how you can quantify the responses, and modify the questions accordingly. Remember, you are conducting a quantitative study. Thus, you will, to some extent, be coding peoples responses as numbers and, quite possibly, conducting statistical analyses on those numbers. You will be able to assign numerical codes to responses more easily if you identify an appropriate coding scheme ahead of time
11. Consider asking questions that will elicit qualitative information as well. You do not necessarily have to quantify everything. Peoples responses to a few open-ended questions may support or provide additional insights into the numerical data you obtain from more structured questions
12. Pilot-test the questions. When you plan your interview, you will, of course, be trying hard to develop clear and concise questions. Despite your best intentions, however, you may write questions that are ambiguous or misleading or that yield uninterpretable or otherwise useless responses. You can save yourself a great deal of time over the long run if you fine-tune your questions before you begin data collection. You can easily find the weak spots in your questions by asking a few volunteers to answer them in a pilot study
13. Restrict each question to a single idea. Dont try to get too much information in any single question in doing so, you may get multiple kinds of data mixed messages, so to speak that are difficult to interpret
14. Save controversial questions for the latter part of the interview. If you will be touching on sensitive topics (e.g., attitudes about AIDS, opinions about gun control), put them near the end of the interview, after you have established rapport and gained the persons trust
15. Seek clarifying information when necessary. Be alert for responses that are vague or otherwise difficult to interpret. Simple probes such as Can you tell me more about that? may produce the additional information you need
Questionnaires seem so simple, yet in our experience they can be tricky to construct and administer
One false step can lead to uninterpretable data or an abysmally low return rate
1. Keep it short. Your questionnaire should be as brief as possible and solicit only that information essential to the research project. You should test every item by two criteria (a) What do I intend to do with the information I am requesting? and (b) Is it absolutely essential to have this information to solve part of the research problem?
2. Use simple, clear, unambiguous language. Write questions that communicate exactly what you want to know. Avoid terms that your respondents may not understand, such as obscure words or technical jargon. Also avoid words that do not have precise meanings, such as several and usually
3. Check for unwarranted assumptions implicit in your questions. Consider a very simple question
How many cigarettes do you smoke each day? It seems to be a clear and unambiguous question, especially if we accompany it with certain choices so that all the respondent has to do is to check one of them
How many cigarettes do you smoke each day? (Check one of the following.)
? More than 25 ? 25-16 ? 15-11
? 10-6 ? 5-1 ? None
One obvious assumption here is that the person is a smoker, which probably is not the case for all participants
A second assumption is that a person smokes the same number of cigarettes each day, but for many smokers, this assumption is not true
At work, if under pressure, they may be chain smokers and may smoke more
But at home on weekends and holidays, they may relax and smoke only one or two cigarettes a day or go without smoking at all
How are the people in this group supposed to answer the above question?
What box does this type of smoker check?
First, you have to inspect the assumption underlying the question Does it fit the reality?
Had the author of the question considered the assumptions on which the question was predicated, he or she might first have asked questions as these
Do you smoke cigarettes?

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Descriptive Research: Methods, Types, and Examples | PPT

In order to understand what descriptive research is, one must first understand the different types of research methods. Descriptive research can be defined as a method used to describe something, usually in great detail. This type of research is often used in the sciences, such as in biology or psychology.

It can also be used in other fields, such as marketing or sociology. There are many different ways to collect data for descriptive research, lets take a look on examples, methods, types, pros and cons of Descriptive Research in this article.

Table of Contents

What is Descriptive Research?

Descriptive research is a type of research that is used to describe a population or phenomenon. This type of research is often used in the social sciences, but can be used in other disciplines as well.

Descriptive research is often used to provide a snapshot of a population or phenomenon. It can also be used to answer questions about how something works or why something happens.

When doing a descriptive study, the researcher thoroughly details the circumstance or case in their research materials. This kind of research design is entirely theoretical, and the researcher gathers data, analyses it, prepares it, and then clearly displays it. It is the type of study design that is the most inclusive.

Descriptive research can be either quantitative or qualitative in nature.

Quantitative descriptive research

Quantitative descriptive research involves collecting data that can be quantified, such as age, gender, income levels, etc. This type of data is typically collected through surveys or other means of data collection.

Qualitative descriptive research

Qualitative descriptive research involves collecting data that cannot be quantified, such as opinions, beliefs, attitudes, etc. This type of data is typically collected through interviews or focus groups.

Examples of Descriptive Research

How the real estate market in London has transformed in the last 20 years ?
Which product C or D are clients of firm A most interested in ?
What distinguishes hybrid cows from Indian wild cows in terms of genetics, behavior, and morphology ?
How common is illness 1 in population Z ?

Characteristics of Descriptive Research

There are many different characteristics of descriptive research, which include:

Quantitative in Nature

In descriptive research, data is systematically and quantitatively collected so that the research problem may be statistically analyzed. It does not involve the manipulation of variables. This type of research is typically quantitative, meaning that it uses numerical data to describe the population or phenomenon.

Observational

Descriptive research is observational in that it simply observes and records what is happening. It does not try to explain why something is happening or to manipulate variables.

Uncontrolled Variables

Descriptive research differs from experimental research in that the variables are not managed or controlled. This is one of its most salient features. Instead, they are only recognized, scrutinized, and measured. It does not involve the manipulation of variables. This means that researchers cannot control what happens during the course of the study.

Basis for Further Research

The data gathered during descriptive research serves as a foundation for subsequent study since it aids in gaining a thorough grasp of the research topic in order to properly respond to it.

Cross-sectional Studies

Cross-sectional studies are typically used to do descriptive research. An observational study method known as a cross-sectional study involves obtaining data on various variables at the person level at a specific period.

Pros of Descriptive Research

Comprehensive.

Descriptive research frequently combines quantitative and qualitative methods, giving the research topic a more detailed knowledge.

Various Data Collection Techniques

The case study method, observational method, and survey method are just a few of the many data collection techniques that can be utilized in descriptive research. Quick and economical.

High External Validity

As research is conducted in the respondent’s natural context with no variables being altered, results generated using the descriptive method of research frequently have high levels of external validity.

Quick and Inexpensive

Since surveys are frequently used in descriptive research, it is possible to quickly, cost efficiently and efficiently collect data from a fairly large sample size.

Cons of Descriptive Research

Unable to validate or test research question.

Due to the fact that the data acquired does not assist in elucidating the reason of the phenomenon being examined, the descriptive technique of research cannot be utilized to test or validate the research problem.

Risk of Sampling Error

When choosing a sample group for a descriptive research study, random sampling is typically used. If the sample group isn’t representative of the larger population, chance may cause sampling error. Results from sampling mistake would be unreliable and unreliable.

Absence of Dependability

The data gathered could not be completely reliable if the research problem isn’t well-formulated. Additionally, this makes conducting a reliable investigation more difficult.

Possibility of False Responses

People’s reactions are crucial to descriptive research, especially when employing surveys. False responses may occasionally be given, which would undermine the reliability of the data gathered and, ultimately, the research’s conclusions.

Pros and Cons of Descriptive Research

Why to use descriptive research, comparing variables.

Descriptive research can be used to compare various variables and the responses of various demographics to various variables.

Validate the Current Conditions

Given that it requires a thorough investigation of each variable before drawing conclusions, descriptive research can be an effective method for determining the validity of an actual condition.

Analysis of Data Trends

The descriptive research approach can be used to track changes in variables over time, enabling the discovery and analysis of trends.

Describe the Features of the Subjects

Additionally, it can be utilized to identify the various traits of the participants. This can include qualities, attitudes, behaviors, and other attributes.

Methods of Descriptive Research

Descriptive research can be qualitative or quantitative in nature, and the researcher may choose to use one or both methods in order to best answer their research question(s). There are many different methods that can be used in descriptive research, and the type of method used will often depend on the type of data being collected.

There are three key methods used to carry out descriptive research.

Observations

Questionnaires or polls are used in survey research to get information from respondents on a particular subject. Since both have advantages, surveys should contain a mix of closed- and open-ended items. Because they may be conducted using a variety of digital and non-digital means, including email, websites, and phone surveys, surveys are a cost-effective technique of data collection.

The case study method entails conducting extensive research on specific people or groups of people. Instead of acquiring a wide volume of data to find correlations and trends, case studies include gathering precise data on a specifically defined subject. Therefore, rather of describing facts that can be generalized, this method is frequently used to describe the various traits of a particular subject.

Researchers can develop hypotheses through case studies that can broaden the scope of evaluation when researching the phenomenon.

With this approach, researchers keep a distance from the subjects they are studying and observe them in their natural environment. This enables them to acquire data on the behaviors and traits under investigation without having to rely on respondents to provide truthful and precise answers.

The observational approach is thought to be the best one for conducting descriptive research. Both qualitative and quantitative data must be gathered.

In conclusion, Descriptive Research is a type of research used to observe and describe phenomena. It is useful in providing detailed information about a specific event, behavior, or group. Although it cannot be used to draw causal relationships, it can be helpful in generating hypotheses for further research.

When deciding whether or not to use Descriptive Research, researchers should consider the pros and cons, as well as the specific research question they are trying to answer.

DESCRIPTIVE RESEARCH

Apr 26, 2012

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DESCRIPTIVE RESEARCH. To behold is to look beyond the fact; to observe, to go beyond the observation Look at the world of people, and you will be overwhelmed by what you see

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DESCRIPTIVE RESEARCH • To behold is to look beyond the fact; to observe, to go beyond the observation • Look at the world of people, and you will be overwhelmed by what you see • But select from that mass of humanity a well-chosen few, and observe them with insight, and they will tell you more than all the multitudes together

Descriptive Quantitative Research • Involves either identifying the characteristics of an observed phenomenon or exploring possible correlations among two or more phenomena • In every case, descriptive research examines a situation AS IT IS • It does not involve changing or modifying the situation under investigation, nor is it intended to determine cause-and-effect relationships • Strategies include sampling, making observations, interviewing – take on a very different form when we want them to yield quantitative data

Descriptive Research Designs • Include observation studies, correlational research, developmental designs, and survey research • All of these approaches yield quantitative information that can be summarized through statistical analyses • Survey research is the most frequently used in all disciplines

Observation Studies • In qualitative studies, observations are usually recorded in great detail, perhaps with fieldnotes or videotapes that capture the wide variety of ways in which people act and interact • From these data, the researcher constructs a complex yet integrated picture of how people spend their time • In quantitative research, an observation study is quite different • Typically, the focus is on a particular aspect of behaviour • Furthermore, the behaviour is quantified in some way • In some situations, each occurrence of the behaviour is counted to determine its overall frequency • In other situations, the behaviour is rated for accuracy, intensity, maturity, or some other dimension • But regardless of approach, the researcher strives to be as objective as possible in assessing the behaviour being studied

Observation Studies • To maintain such objectivity, he or she is likely to use strategies such as the following: 1) Define the behaviour being studied in a precise, concrete manner so that the behaviour is easily recognised when it occurs 2) Divide the observation period into small segments and then record whether the behaviour does or does not occur during each segment 3) Use a rating scale to evaluate the behaviour in terms of specific dimensions 4) Have two or three people rate the same behaviour independently, without knowledge of one another’s ratings 5) Train the rater(s) to follow specific criteria when counting or evaluating the behaviour, and continue training until consistent ratings are obtained for any single occurrence of the behaviour

Observation Studies • Despite the extensive investment (time and energy), an observational study can yield data that portray much of the richness and complexity of human behaviour • In some situations, then, it provides a quantitative alternative to such approaches as ethnographies and grounded theory studies

Correlational Research • A correlational studyexamines the extent to which differences in one characteristic or variable are related to differences in one or more other characteristics or variables • A correlation exists if, when one variable increases, another variable either increases or decreases in a somewhat predictable fashion

Correlational Research • Simple correlation – researchers gather data about two or more characteristics; numbers that reflect specific measurements of the characteristics in question – test scores, CGPAs, ratings, … • Each has two numbers, used to calculate correlation coefficient (r) • If perfectly correlated r = +1.00 or r = -1.00 • If unrelated or remotely related, r is close to 0 • Moderate correlations are common

Correlational Research • Examining only two variables – helpful to plot on scatterplot (also known as scattergram) to allow a visual inspection of the relationship between the two variables • Refer to page 181 of the textbook for the scatterplot • The diagonal line running through the middle of the dots is called the line of regression reflects a hypothetical perfect correlation • If all the dots fell exactly on this line, r would be +1.00, dots below the line show children whose reading level is advanced for their age, and dots above the line show children who are lagging a bit in reading

Correlational Research Can make 3 statements from the scatterplot. 1) Can describe the homogeneity or heterogeneity of the two variables (the extent to which the children are similar to or different from one another with respect to age and reading level. Eg. group of only age 6 and 7 has greater homogeneity than group of age 6 - 13) 2) Can describe the degree to which the two variables are intercorrelated by computing the correlation coefficientr 3) The most important, we can interpret the data and give them meaning – children’s reading level improves as they grow older, without hesitation as shown by the upward trend of the dots from left to right

A Caution About Interpreting Correlational Results • In all correlational studies, be alert for faulty logic • Correlation does not, in and of itself, indicate causation • Although in some cases, influence may indeed be present, for example, chronological age influences mental development, including their reading ability • But ultimately we can never infer a cause-and-effect relationship on the basis of correlation alone

A Caution About Interpreting Correlational Results • One variable correlates meaningfully with another only when a common causal bond links the phenomena of both variables in a logical relationship • Increase in the population of birds in Tasik Serdang has no meaningful relationship with the increase of the population of elephants in Thailand – the correlation is simply a fluke and meaningless

A Caution About Interpreting Correlational Results • In the example, the faulty logic is readily apparent, yet we often see similarly faulty reasoning proposed in correlational research reports • Imagine that a researcher finds a correlation between socioeconomic level and academic performance - it would be all too easy to draw the conclusion that socioeconomic status directly affects academic achievement – also if we could improve the family’s economic status, then the learning ability of the family’s children would also improve

A Caution About Interpreting Correlational Results • No, no, no! We cannot make an inference about causation on the basis of correlated data alone • It is possible that salary does have an impact on children’s grades, BUT it is equally possible that it does not • May be an undetermined third variable influences BOTH the salary and the children’s school performance • If we were to infer that socioeconomic status directly affects academic achievement, not only would we be going far beyond the data we have, but we would also have trouble accounting for all of the world’s geniuses and intellectual giants, some of whom have been born of indigent parents and grown up in poverty

A Caution About Interpreting Correlational Results • The data may not lie, but the causal conclusions we draw from the data may, at times, be extremely suspect • Nevertheless, a good researcher must not be content to stop at the point of finding a correlational relationship, because beneath the correlation lie some potentially quite interesting data whose interpretation may conceivably lead to the discovery of new and exciting information • r is just a signpost pointing to further findings

A Caution About Interpreting Correlational Results • The forces of the correlated data will determine the ultimate meaning of the correlation

How Validity and Reliability Affect Correlation • We will not find correlation if the measurement instruments have poor validity and reliability • For example, if the reading test used is neither a valid (accurate) nor reliable (consistent) measure of reading achievement, therefore we will not find correlation

Developmental Designs • To study how a particular characteristic changes, use either 1) a cross-sectional (X-S) study or 2) a longitudinal (LG) study • In a cross-sectional study, a developmental psychologist might study the nature of friendships for children at ages 4, 8, 12, and 16. A gerontologist might consider how retired people in their 70s, 80s, and 90s, are most likely to spend their leisure time

Developmental Designs • In a longitudinal study, a single group of people is followed over the course of several months or years, and data related to the characteristic(s) under investigation are collected at various times • For example, an educational psychologist might get measures of academic achievement and social adjustment for a group of Year Four students and then, 10 years later, find out which students had completed high school and which ones had not

Developmental Designs • Obviously, cross-sectional studies are easier to conduct than longitudinal studies, because the researcher can collect all the needed data at a single time, and don’t have to worry tracking down people • An additional disadvantage of a longitudinal design is that when people respond repeatedly to the same measurement instrument, they are likely to improve simply because of their practice with the instrument, even if the characteristic being measured hasn’t changed at all

Developmental Designs • A disadvantage of cross-sectional designs is that the different age groups sampled may have been raised under different environmental conditions • Groups of 20-year-olds and 70-year-olds – different education standards • A second disadvantage of a cross-sectional design is that we cannot compute correlations between characteristics at different age levels

Survey Research • Survey means “to look or see over or beyond” • “Looking” or “seeing” is not restricted to perception through the physical eye only • Survey research involves acquiring information about one or more groups of people – perhaps about their characteristics, opinions, attitudes, or previous experiences – by asking them questions and tabulating their answers • The ultimate goal is to learn about a large population by surveying a sample of that population

Survey Research • This approach is called a descriptive survey or normative survey • Reduced to its basic elements, a survey is quite simple in design: The researcher poses a series of questions to willing participants; summarises their responses with percentages, frequency counts, or more sophisticated statistical indexes; and then draws inferences about a particular population from the responses of the sample • It is a common approach, used with more or less sophistication in many areas of human activity

Survey Research • This is not to suggest, however, that because of its frequent use, a survey is any less demanding in its design requirements or any easier for the researcher to conduct than any other type of research • Quite the contrary, the survey design makes critical demands on the researcher that, if not carefully respected, may place the entire research effort in jeopardy

Survey Research • Survey research captures a fleeting moment in time • By drawing conclusions from one transitory collection of data, we may extrapolate about the state of affairs over a longer time period • At best, the extrapolation is a conjecture, and sometimes a hazardous one at that, but it is our only way to generalise from what we see • So often, survey reports that we read seem to suggest that what the researcher found in one sample population at one particular time can be accepted for all time as a constant

Survey Research • An additional consideration in survey research is that we are relying on self-report data • People are telling us what they believe to be true or, perhaps, what they think we want to hear • People’s memories for events are often distortions of reality: What they think happened isn’t always what did happen • Furthermore, people’s descriptions of their attitudes and opinions are often constructed on the spot – often times, they haven’t really thought about certain issues until a researcher poses a question about them – and so may be coloured by recent events or the current context

Survey Research • An additional problem is that some people may intentionally misrepresent the facts (at least, the “facts” as they know them) in order to present a favourable impression to the researcher • Survey research typically employs a face-to-face interview, a telephone interview, or a written questionnaire

Face-to-Face and Telephone Interviews • In survey research, interviews are fairly structured • In a structured interview, the researcher asks a standard set of questions and nothing more • In a semi-structured interview, the research may follow the standard questions with one or more individually tailored questions to get clarification or probe a person’s reasoning • The interview tends to be informal and friendly in a qualitative study but more formal and emotionally neutral in a quantitative one • Participants in a qualitative interview may feel as if they’re simply engaging in a friendly chat with the researcher, who is typically someone they’ve come to know and trust

Face-to-Face and Telephone Interviews • In contrast, participants in survey research are continually aware that, yes, this is an interview, and that the temporary relationship they’ve formed with the researcher will end once the interview is complete • This is not to say, however, that a survey researcher shouldn’t strive to establish rapport with participants • Quite the contrary, the researcher is more likely to gain participants’ cooperation and encourage them to respond honestly if he or she is likable and friendly and shows a genuine interest in what they have to say

Face-to-Face and Telephone Interviews • Face-to-face interviews have the distinct advantage of enabling the researcher to establish rapport with potential participants and therefore gain their cooperation; thus, such interviews yield the highest response rates – the percentages of people agreeing to participate – in survey research • However, the time and expense involved may be prohibitive if the needed interviewees reside in a variety of states and countries

Face-to-Face and Telephone Interviews • Telephone interviews are less time-consuming and less expensive (they involve only the cost of long-distance calls), and the researcher has ready access to virtually anyone on the planet who has a telephone • Although the response rate is not as high as for a face-to-face interview (many people are apt to be busy, annoyed at being bothered, or otherwise not interested in participating), it is considerably higher than for a mailed questionnaire • The researcher cannot establish the same kind of rapport that is possible in a face-to-face situation, and the sample will be biased to the extent that people without phones are part of the population about whom the researcher wants to draw inferences • Personal interviews, whether they be face-to-face or over the telephone, allow the researcher to clarify ambiguous answers and, when appropriate, seek follow-up information • Because such interviews take time, however, they may not be practical when large sample sizes are important

Questionnaires • Data lie deep within the minds or attitudes, feelings, or reaction of men/women • Instrument for observing the data beyond the physical reach is the questionnaires since paper-pencil questionnaires can be sent to a large number of people, including those who live thousands of miles away • Thus, they may save the researcher travel expenses, and postage is typically cheaper than a lengthy long-distance telephone call • The social scientist who collects data with a questionnaire and the physicist who determines the presence of radioactivity with a Geiger counter are at just about the same degree of remoteness from their respective sources of data: Neither sees the source from which the data originate • The Geiger counter and questionnaires are impersonal probe • They are governed by practical guidelines

Questionnaires • From the perspective of survey participants, this distance becomes an additional advantage: Participants can respond to questions with assurance that their responses will be anonymous, and so they may be more truthful than they would be in a personal interview, particularly when they are talking about sensitive or controversial issues • Yet questionnaires have their drawbacks as well • Typically, the majority of people who receive questionnaires don’t return them – in other words, there may be a low return rate – and the people who do return them are not necessarily representative of the originally selected sample • Even when people are willing participants in a questionnaire study, their responses will reflect their reading and writing skills and, perhaps, their misinterpretation of one or more questions • Furthermore, by specifying in advance all of the questions that will be asked – and thereby eliminating other questions that could be asked about the issue or phenomenon in question – the researcher is apt to gain only limited, and possibly distorted, information

Using Checklists and Rating Scales • Observation studies look at people’s behaviours, and developmental studies, correlational studies, and survey research frequently use questionnaires to learn about people’s behaviours, characteristics, attitudes, and opinions • Behaviours and attitudes are often quite complex and so not, at least on the surface, easily evaluated or quantified • Two techniques that facilitate both evaluation and quantification in such circumstances are the checklist and the rating scale • A checklist is a list of behaviours, characteristics, or other entities that a researcher is investigating. Either the researcher or participants (depending on the study) simply check(s) whether each item on the list is observed, present, or true; or else not observed, present, or true

Using Checklists and Rating Scales • A rating scale is more useful when a behaviour, attitude, or other phenomenon of interest needs to be evaluated on a continuum of, say, “inadequate” to “excellent”, “never” to “always”, or “strongly disapprove” to “strongly approve” • Rating scales were developed by Rensis Likert in the 1930s to assess people’s attitudes; accordingly, they are sometimes called Likert scales • Experts have mixed views about letting respondents remain neutral in interviews and questionnaires • If you use rating scales in your own research, you should consider the implications of letting your respondents”straddle the fence” by including a “no opinion” or other neutral response, and design your scales accordingly

Using Checklists and Rating Scales • Whenever you use checklists or rating scales, you simplify and more easily quantify people’s behaviours and attitudes • In the process, however, you may lose valuable information • Ultimately you will have to determine whether the trade-offs is worth it for the particular research problem you are investigating

Planning and Conducting Interviews • Interviewing involves much more than just asking questions • The questions for the interview should be carefully planned and precisely worded to yield the kinds of data the researcher needs to answer his or her research question

Guidelines for Conducting Interviews in a Quantitative Study • Make sure your interviewees are representative of the group • Find a suitable location • Get written permission • Establish and maintain rapport • Focus on the actual rather than on the abstract or hypothetical • Don’t put words in people’s mouths • Record responses verbatim • Keep your reactions to yourself • Remember that you are not necessarily getting the facts But interviews are typically more structured in quantitative studies than they are in qualitative studies. The following are additional guidelines for conducting interviews in quantitative research

Guidelines for Conducting Interviews in a Quantitative Study 10. As you write the questions, consider how you can quantify the responses, and modify the questions accordingly. Remember, you are conducting a quantitative study. Thus, you will, to some extent, be coding people’s responses as numbers and, quite possibly, conducting statistical analyses on those numbers. You will be able to assign numerical codes to responses more easily if you identify an appropriate coding scheme ahead of time 11. Consider asking questions that will elicit qualitative information as well. You do not necessarily have to quantify everything. People’s responses to a few open-ended questions may support or provide additional insights into the numerical data you obtain from more structured questions

Guidelines for Conducting Interviews in a Quantitative Study 12. Pilot-test the questions. When you plan your interview, you will, of course, be trying hard to develop clear and concise questions. Despite your best intentions, however, you may write questions that are ambiguous or misleading or that yield uninterpretable or otherwise useless responses. You can save yourself a great deal of time over the long run if you fine-tune your questions before you begin data collection. You can easily find the weak spots in your questions by asking a few volunteers to answer them in a pilot study 13. Restrict each question to a single idea. Don’t try to get too much information in any single question; in doing so, you may get multiple kinds of data – “mixed messages”, so to speak – that are difficult to interpret

Guidelines for Conducting Interviews in a Quantitative Study 14. Save controversial questions for the latter part of the interview. If you will be touching on sensitive topics (e.g., attitudes about AIDS, opinions about gun control), put them near the end of the interview, after you have established rapport and gained the person’s trust 15. Seek clarifying information when necessary. Be alert for responses that are vague or otherwise difficult to interpret. Simple probes such as “Can you tell me more about that?” may produce the additional information you need

Constructing and Administering a Questionnaire • Questionnaires seem so simple, yet in our experience they can be tricky to construct and administer • One false step can lead to uninterpretable data or an abysmally low return rate

Guidelines for Constructing a Questionnaire 1. Keep it short. Your questionnaire should be as brief as possible and solicit only that information essential to the research project. You should test every item by two criteria: (a) What do I intend to do with the information I am requesting? and (b) Is it absolutely essential to have this information to solve part of the research problem? 2. Use simple, clear, unambiguous language. Write questions that communicate exactly what you want to know. Avoid terms that your respondents may not understand, such as obscure words or technical jargon. Also avoid words that do not have precise meanings, such as several and usually

Guidelines for Constructing a Questionnaire 3. Check for unwarranted assumptions implicit in your questions. Consider a very simple question: “How many cigarettes do you smoke each day?” It seems to be a clear and unambiguous question, especially if we accompany it with certain choices so that all the respondent has to do is to check one of them: How many cigarettes do you smoke each day? (Check one of the following.)  More than 25  25-16  15-11  10-6  5-1  None • One obvious assumption here is that the person is a smoker, which probably is not the case for all participants • A second assumption is that a person smokes the same number of cigarettes each day, but for many smokers, this assumption is not true • At work, if under pressure, they may be chain smokers and may smoke more

Guidelines for Constructing a Questionnaire • But at home on weekends and holidays, they may relax and smoke only one or two cigarettes a day or go without smoking at all • How are the people in this group supposed to answer the above question? • What box does this type of smoker check? • First, you have to inspect the assumption underlying the question: Does it fit the reality? • Had the author of the question considered the assumptions on which the question was predicated, he or she might first have asked questions as these: “Do you smoke cigarettes? Yes No (If you mark “no”, skip the next two questions.) “Are your daily smoking habits reasonably consistent; that is, do you smoke about the same number of cigarettes each day?” Yes No (If you mark “no”, skip the next question.)

Guidelines for Constructing a Questionnaire 4. Word your questions in ways that do not give clues about preferred or more desirable responses. Take another question: “What strategies have you used to try to quit smoking?” By implying that the respondent has, in fact, tried to quit, it may lead him or her to describe strategies that have never been seriously tried at all 5. Check for consistency. When an issue about which you are asking is such that some respondents may give answers that are socially acceptable rather than true, you may wish to incorporate a “countercheck” question into your list at some distance from the first question. This strategy helps verify the consistency with which a respondent has answered questions. For instance, take the following two items appearing in a questionnaire as items 2 and 30. (Their distance from each other increases the likelihood that a person will answer the second without recalling how he or she answered the first.)

Guidelines for Constructing a Questionnaire Notice how one individual has answered them: 2. Check one of the following choices:  In my thinking, I am a socialist. __ In my thinking, I am a capitalist. 30. Check one of the following choices: __ I believe that major economic activities must be owned by the state.  I believe that major economic activities must be owned by private owners. The two responses are inconsistent. In the first, the respondent claims to be a socialist but later, when given the socialist and the capitalist positions in another form, indicates a position generally thought to be more capitalist than socialist. Such an inconsistency might lead you to question whether the respondent is truly the socialist thinker that he or she claims to be

Guidelines for Constructing a Questionnaire 6. Determine in advance how you will code the responses. As you write your questions, perhaps even before you write them, develop a plan for recoding participants’ responses into numerical data that you can statistically analyse. Data processing procedures may also dictate the form a questionnaire should take. If, for example, people’s response sheets will be fed into a computer scanner, the questionnaire must be structured differently than if the responses will be tabulated using paper and pencil

Guidelines for Constructing a Questionnaire 7. Keep the respondent’s task simple. Make the instrument as simple to read and respond to as possible. Remember, you are asking for people’s time, a precious commodity for many people these days • Discussion items – those that present open-ended questions and ask people to respond with lengthy answers – are time-consuming and mentally exhausting for both the participants and the researcher. Don’t forget that you will have to wrestle with the participants’ words to try to determine exactly what their answers mean. Those who write in the “Yes/no, and I’ll tell you why” style are few and far between. The usefulness of responses to discussion items rests entirely on participants’ skill to express in words the thoughts they wish to convey. Respondents may ramble, engaging in discussion that doesn’t answer the question or is beside the point • Save your respondents and yourself from this ordeal. After answering 15 to 20 discussion questions, your respondents will think you are demanding a book! Such a major compositional exercise is unfair to those from whom you are requesting a favour

Guidelines for Constructing a Questionnaire 8. Provide clear instructions. Communicate exactly how you want people to respond. For instance, don’t assume that they are familiar with Likert scales. Some of them may never have seen such scales before 9. Give a rationale for any items whose purpose may be unclear. We can’t say this enough: You are asking people to do you a favour by responding to your questionnaire. Give them a reason to want to do the favour. At a minimum, each question should have a purpose, and in one way or another, you should make that purpose clear 10. Make the questionnaire attractive and professional looking. Your instrument should have clean lines, crystal-clear typing (and certainly no typos!), and, perhaps, two or more colours

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67 Types of Quantitative Data Analysis and Presentation Format

If your thesis is quantitative research, you will be conducting various types of analyses (see the following table).

Practicing and Presenting Social Research Copyright © 2022 by Oral Robinson and Alexander Wilson is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Description

Basic concepts and models for research methodology applied to the analysis of data in social work. Emphasis is on quantitative analysis, using statistics software. Qualitative research is also incorporated. (Prerequisite: ScWk 240, 3 Units).

ScWk 242 Section 5 Syllabus (PDF)

Course outline for the Spring 2013 ScWk 242 Section 5 class

ScWk 242 Section 5 Course Outline Spring 2013 [PDF]

Weekly Session Overhead Slides

Session 1 Slides ppt - Introduction and Review [PPT]
Session 1 Slides pdf - Introduction and Review [PDF]
Session 2 Slides - Review of Qualitative Research and Analysis ppt [PPT]
Session 2 Slides - Review of Qualitative Research and Analysis pdf [PDF]
Session 3 Slides - Interviewing ppt version [PPT]
Session 3 Slides - Interviewing pdf version [PDF]
Transcultural Slides from HBSE (for Session 3 Reference Only) [PDF]
Session 4 Slides - Focus Groups ppt version [PPT]
Session 4 Slides - Focus Groups pdf version [PDF]
Session 5 Slides - Observation - pptx version [PPTX]
Session 5 Slides - Observation - pdf version [PDF]
Session 6 Slides - Intro to Quantitative Research & SPSS ppt version [PPT]
Session 6 Slides - Intro to Quantitative Research & SPSS pdf version [PDF]
Session 7 Slides - Quantitative Analysis - Chi-Square [PPT]
Session 7 Slides - Quantitative Analysis - Chi Square [PDF]
Session 8 Slides - Descriptive Statistics Using SPSS - ppt version [PPT]
Session 8 Slides - Descriptive Statistics Using SPSS - pdf version [PDF]
Session 9 Slides - Inferential Statistics and t-tests - ppt version [PPTX]
Session 9 Slides - Inferential Statistics and t-tests - pdf version [PDF]
Session 10 Slides - Evaluation Research and Logic Models - pptx version [PPTX]
Session 10 Slides - Evaluation Research and Logic Models - pdf version [PDF]
Session 11 Slides - Program Evaluation and Data Analysis - pptx version [PPTX]
Session 11 Slides - Program Evaluation and Analysis - pdf version [PDF]
April 17 Class Slides - ANOVA and Linear Regression - ppt version [PPT]
April 17 Class Slides - ANOVA and Linear Regression - pdf version [PDF]
Session 14 Slides - Final Paper - pptx version [PPTX]
Session 14 Slides - Final Paper - pdf version [PDF]
Session 16 Slides - Wrap UP - pptx version [PPTX]
Session 16 Slides - Wrap-Up - pdf version [PDF]

Online Reading Assignments

The attached word document includes links to all of the supplemental readings that are available online. The readings are listed weekly in chronological order.

Document with Weekly Online Reading Links [DOCX]
Session 2 Reading - Chapter 12 Qualitative Research [PDF]
Session 2 Reading - Chapter 12 Multiple Choice Q & A [PDF]
Session 2 Reading - Chapter 12 Study Q & A [PDF]
Session 2 Reading - Chapter 17 Qualitative Research [PDF]
Session 2 Reading - Chapter 17 Study Questions [PDF]
Session 2 Readings - Chapter 17 Study Question Answers [PDF]
Session 3 Reading - Turner - Qualitative Interview Guide [PDF]
Session 4 Reading - Utah Department of SA & MH - Focus Groups [PDF]
Session 4 Reading - New York State Teachers - Focus Groups [PDF]
Session 5 Reading - Duke University Field Observation Guide - pdf [PDF]
Weeks 10 & 11 Reading - Logic Model [PDF]
Weeks 10 & 11 Reading - United Way [PDF]

Assignments

Qualitative Analysis Lab 1 - Done on Class on 2/6 and due on 2/13 [DOCX]
Qualitative Analysis Lab 2 - Done in Class on 2/13 and Due on 2/20 [DOCX]
Qualitative Lab 3 - Done in Class on 2/20 [DOCX]
CASA Writing Assistance Flyer - Place and Times [DOC]
Quantitative Lab 1 Assignment: Chi-Square [DOC]
Sample Table Formats [DOC]
Session 8 - Class Exercise - Descriptive Statistics Using SPSS [DOCX]
Session 8 Class Exercise - Copy of Questionnaire [PDF]
Session 8 - Class Exercise SAMHSA Dataset [SAV]
Session 8 SAMHSA Frequency Tables [DOCX]
Lab 2 - Independent t-test - Done in-Class March 20 and due March 24 [DOC]
Program Evaluation Paper Assignment - Due on April 17 [DOCX]
Logic Model Template for Program Evaluation [DOC]
Session 10 In-Class Exercise - Program Evaluation - pptx version [PPTX]
Session 10 In-Class Exercise - Program Evaluation - pdf version [PDF]
Session 11 In-Class Group Assignment - Program Evaluation [DOCX]
April 17 In-Class Exercise - ANOVA [DOC]
Study Guide for In-Class Exam on May 1 [DOC]
Final Paper Assignment Instructors - Assignment Due on May 8 [DOC]

Online Resources

APA Formatting 6th Edition Summary [DOC]
Final Paper Self Grading/Evaluation Rubric [DOCX]
Writing Guide [DOC]
Writing Tips - Paraphrazing [DOCX]
Writing Tips - Paraphrazing 2 [DOCX]

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Quantitative Data Presentation and Analysis: Descriptive Analysis

First Online: 01 October 2022

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Charitha Harshani Perera 4 ,
Rajkishore Nayak 5 &
Long Van Thang Nguyen 6

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This chapter provides a descriptive analysis of the quantitative data and is divided into five sections. The first section presents the preliminary consideration of data, showing the response rate and the process of data screening and cleaning.

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Faculty of Business and Law, Northumbria University, Newcastle upon Tyne, United Kingdom

Charitha Harshani Perera

School of Communication and Design, RMIT University, Ho Chi Minh City, Vietnam

Rajkishore Nayak

Long Van Thang Nguyen

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Perera, C.H., Nayak, R., Nguyen, L.V.T. (2022). Quantitative Data Presentation and Analysis: Descriptive Analysis. In: Social Media Marketing and Customer-Based Brand Equity for Higher Educational Institutions. Springer, Singapore. https://doi.org/10.1007/978-981-19-5017-9_5

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Descriptive research
Jul 10, 2011 • Download as PPTX, PDF •. 182 likes • 233,247 views. M. Markquee Alceso. DESCRIPTIVE RESEARCH. Technology Health & Medicine. Slideshow view. Download now. Descriptive research - Download as a PDF or view online for free.
PPT
Presentation Transcript. Quantitative Research Counting, and reporting. Quantitative Research • Numbers-based - Quantitative research refers to the manipulation of numbers to make claims, provide evidence, describe phenomena, determine relationships, or determine causation. • Deductive - usually tests a hypothesis based on previous ...
Descriptive Research
Descriptive research methods. Descriptive research is usually defined as a type of quantitative research, though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable.. Surveys. Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages ...
Experimental research design
2. The purpose of descriptive studies is to describe individuals, events, or conditions by studying them as if they are in nature. The researcher does not manipulate medical data collection variables but only describes the sample and the variables. Although a descriptive study can explore multiple variables, it is the only research design that can also explore a single variable.
PDF 3. Descriptive statistics.ppt
Range: Difference between largest and smallest observations (but highly sensitive to outliers, insensitive to shape) Standard deviation: A "typical" distance from the mean. The deviation of observation i from the mean is. i y − y. The variance of the n observations is. 2 s = i n − 1. = n − y ( + 1 + 2. y. n − 1.
Quantitative research
Jan 11, 2016 • Download as PPTX, PDF •. 164 likes • 178,245 views. Tooba Kanwal. This presentation is about Quantitative Research, its types and important aspects including advantages and disadvantages, characteristics and definitions. Education. 1 of 32. Download now. Quantitative research - Download as a PDF or view online for free.
PDF Lecture 2: Descriptive Statistics and Exploratory Data Analysis
Scale: Quartiles and IQR. 25%25% 25% 25%. •The ﬁrst quartile, Q. 1. , is the value for which 25% of the observations are smaller and 75% are larger •Q. 2. is the same as the median (50% are smaller, 50% are larger) •Only 25% of the observations are greater than the third quartile. Q. 1Q.
DESCRIPTIVE RESEARCH DESIGN OVERVIEW
DESCRIPTIVE-RESEARCH-DESIGN.pptx - Free download as Powerpoint Presentation (.ppt / .pptx), PDF File (.pdf), Text File (.txt) or view presentation slides online. Descriptive research is a quantitative research method that describes the characteristics of a population or phenomenon without determining why something occurs. It focuses on describing what is happening rather than explaining why.
DESCRIPTIVE RESEARCH
Title: DESCRIPTIVE RESEARCH. 1. DESCRIPTIVE RESEARCH. To behold is to look beyond the fact to observe, to go beyond the observation. Look at the world of people, and you will be. overwhelmed by what you see. But select from that mass of humanity a. well-chosen few, and observe them with insight,
Descriptive Research: Methods, Types, and Examples
Descriptive research can be defined as a method used to describe something, usually in great detail. This type of research is often used in the sciences, such as in biology or psychology. It can also be used in other fields, such as marketing or sociology. There are many different ways to collect data for descriptive research, lets take a look ...
DESCRIPTIVE RESEARCH PowerPoint Presentation, free download
Descriptive Research Designs • Include observation studies, correlational research, developmental designs, and survey research • All of these approaches yield quantitative information that can be summarized through statistical analyses • Survey research is the most frequently used in all disciplines.
Study designs: Part 2
INTRODUCTION. In our previous article in this series, [ 1] we introduced the concept of "study designs"- as "the set of methods and procedures used to collect and analyze data on variables specified in a particular research question.". Study designs are primarily of two types - observational and interventional, with the former being ...
Descriptive Statistics
Descriptive statistics summarize and organize characteristics of a data set. A data set is a collection of responses or observations from a sample or entire population. In quantitative research, after collecting data, the first step of statistical analysis is to describe characteristics of the responses, ...
Descriptive Research
9. Observational Method The observational method is the most effective method to conduct descriptive research and both quantitative observation and qualitative observation are used in this research method. Quantitative observation is the objective collection of data which is primarily focused on numbers and values - it suggests "associated to, of or depicted in terms of a quantity ...
Descriptive Quantitative Research PowerPoint Presentation and Slides
Create a dynamic yet engaging management presentation with Descriptive Quantitative Research presentation templates and Google slides. Toggle Nav. Search. Search. Search . 5. Notifications 5. SlideTeam added 415 new ... Access our PowerPoint Ebooks and become a brilliant presentation designer. 3 days ago. SlideTeam added 2 new products (e.g ...
(PPT) QUANTITATIVE RESEARCH METHODS AND DESIGN
Aim of the study: The present study aimed to evaluate the effect of cognitive behavioral (CB) intervention on improving sleep quality in older adults. Design: A quasi-experimental pretest-and-posttest design was utilized to conduct this study. Setting: The study was conducted in the geriatric social club in Zagazig City.
Types of Quantitative Data Analysis and Presentation Format
If your thesis is quantitative research, you will be conducting various types of analyses (see the following table). Table 10.1 - Some Common Forms of Quantitative Analysis; Type of Analysis: Appropriate Quantitative Analysis: Presentation Format: Univariate: Descriptive statistics (range, mean, median, mode, standard deviation, skewness ...
Quantitative Research Methods For Descriptive Analysis
It include details such as experiment, survey, systematic observation, secondary research. Introducing our Quantitative Research Methods For Descriptive Analysis set of slides. The topics discussed in these slides are Qualitative Research Methods, Experiment. This is an immediately available PowerPoint presentation that can be conveniently ...
DESCRIPTIVE DESIGN
8. • In case of descriptive studies bias is prevented through operational definitions of variables, by choosing a large sample size, by using random sampling techniques, By means of using a valid & reliable tools of measurement, & formal data collection procedures.
ScWk 242
Session 6 Slides - Intro to Quantitative Research & SPSS pdf version [PDF] Session 7 Slides - Quantitative Analysis - Chi-Square [PPT] Session 7 Slides - Quantitative Analysis - Chi Square [PDF] Session 8 Slides - Descriptive Statistics Using SPSS - ppt version [PPT] Session 8 Slides - Descriptive Statistics Using SPSS - pdf version [PDF ...
Quantitative Data Presentation and Analysis: Descriptive Analysis
5.1 Introduction. This chapter provides a descriptive analysis of the quantitative data and is divided into five sections. The first section presents the preliminary consideration of data, showing the response rate and the process of data screening and cleaning. The second section deals with the demographic profiles of the respondents.
Descriptive statistics ppt
Descriptive statistics ppt. Mar 18, 2022 • Download as PPT, PDF •. 0 likes • 722 views. Titus Mutambu Mweta. dstssd. Data & Analytics. 1 of 38. Download now. Descriptive statistics ppt - Download as a PDF or view online for free.
Descriptive Research PowerPoint Presentation and Slides
Presenting Descriptive Quantitative Research Ppt Powerpoint Presentation Visual Aids Cpb slide which is completely adaptable. The graphics in this PowerPoint slide showcase seven stages that will help you succinctly convey the information. In addition, you can alternate the color, font size, font type, and shapes of this PPT layout according to ...

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DESCRIPTIVE RESEARCH

Descriptive Research: Methods, Types, and Examples | PPT

What is Descriptive Research?

Quantitative descriptive research

Qualitative descriptive research

Examples of Descriptive Research

Characteristics of Descriptive Research

Quantitative in Nature

Observational

Uncontrolled Variables

Basis for Further Research

Cross-sectional Studies

Pros of Descriptive Research

Various Data Collection Techniques

High External Validity

Quick and Inexpensive

Cons of Descriptive Research

Risk of Sampling Error

Absence of Dependability

Possibility of False Responses

Pros and Cons of Descriptive Research

Validate the Current Conditions

Analysis of Data Trends

Describe the Features of the Subjects

Methods of Descriptive Research

Observations

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