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Quantitative Research: Definition, Methods, Types and Examples

What is quantitative research? Quantitative research is defined as a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects information from existing and potential customers using sampling methods and sending out online surveys, online polls, questionnaires, etc., the results of which can be depicted in

8 Comments

09
Sep
Types of quantitative methods

Quantitative methods represent the steps of using the Scientific Method of research. There are following types of quantitative method… 1. Experimental Research is the most well-established quantitative methodology in both the physical and social sciences. This approach uses the principles of research in the physical sciences to conduct experiments that explore human behavior. 2.

09
Sep
Difference Between Qualitative and Quantitative Research

If the subject into which you conduct research is a scientific subject or topic, then the research methods include experiments, tests, the study of many other results of different experiments performed earlier about the topic or the subject and the like. On the other hand, research methodology about the scientific topic involves the techniques

09
Sep
Questionnaire survey for quantitative research

Survey vs Questionnaire: Differences and Definitions A questionnaire is used to collect data from a list of questions. It’s not used to look for trends, behavior or a bigger picture. A survey is data collection through a set of questions for the purposes of statistical analysis To put it simply – a questionnaire is a

23
Oct
Content Analysis Method and Examples

Content analysis is a research tool used to determine the presence of certain words, themes, or concepts within some given qualitative data (i.e. text). Using content analysis, researchers can quantify and analyze the presence, meanings and relationships of such certain words, themes, or concepts. As an example, researchers can evaluate language used within a

23
Oct
Introduction to Statistical Data Analysis

Statistics is basically a science that involves data collection, data interpretation and finally, data validation. Statistical data analysis is a procedure of performing various statistical operations. It is a kind of quantitative research, which seeks to quantify the data, and typically, applies some form of statistical analysis. Quantitative data basically involves descriptive data, such as survey

23
Oct
Meta-analysis in management research

"Meta-analysis is the statistical combination of results from two or more separate studies" (Deeks et al, 2019, chapter 10). When the treatment effect (or effect size) is consistent from one study to the next, meta-analysis can be used to identify this common effect. When the effect varies from one study to the next, meta-analysis may be used to identify the reason for the

23
Oct
Choosing a Research Approach: Qualitative or Quantitative?

Researchers have to decide what type of approach they want to use to collect and to analyze their data. In other words, how they are going to tackle the empirical side of their research. We begin this section by examining what distinguishes a qualitative from a quantitative approach. We then show how these two

26
Jul
A Definition of Content Analysis

In content analysis, evaluators classify the key ideas in a written communication, such as a report, article, or film. Evaluators can do content analysis of video, film, and other forms of recorded information, but in this paper, we focus on analyzing words. Here is a formal definition of content analysis: it is a systematic

18
Aug
The Uses of Content Analysis

Here are several ways in which GAO evaluators have successfully used content analysis techniques. In Stars and Stripes: Inherent Conflicts Lead to Allegations of Military Censorship (GAO, 1988), GAO evaluators used content analysis to help assess issues of censorship, news management, and other influences on various editions of the military newspaper. Details of technique

18
Aug
Computerized Content Analysis

The increasing availability of written information on computer files, and the increasing number of computer programs to analyze text files, makes content analysis easier to do than ever before. Moreover, computerized programs can easily code textual data and combine them with quantitative data. The evaluator can then analyze both kinds of data with various

18
Aug
Some Advantages of Content Analysis

1. It Can Be Unobtrusive One problem with surveys and some experimental methods is that evaluators and their informants can interact during data collection in ways other than how they would “naturally” react. For example, a content analysis of the hearing transcripts might be more useful than interviews with federal officials about what took

18
Aug
Some Disadvantages of Content Analysis

Because content analysis is systematic, sufficient human resources must be committed to it and rigorously applied to it. This may mean, for some evaluation applications, that the benefits may not outweigh the cost of the resources. Moreover, while content analysis has safeguards against distortion of the evidence, evaluators must use judgment in coding the

18
Aug
How to Apply Content Analysis

GAO evaluators can use content analysis to articulate a program’s objectives, describe its activities, and determine its results. 1. Program Objectives Many evaluations characterize a program’s objectives. For example, evaluators might compare a program’s legislative objectives with those of the executive branch. To do this, they might gather written or tape-recorded information from the

18
Aug
Assignment Objectives of Content Analysis

GAO often expresses an assignment’s objectives in the form of three broad categories of evaluation question: descriptive, normative, or impact questions. (GAO, 1991c) In theory, content analysis can address all three categories. In practice, descriptive and normative questions are especially amenable to content analysis; program impact questions are less commonly answered through content analysis.

18
Aug
Data Available or to Be Collected for Content Analysis

Whether or not content analysis is appropriate depends on the nature of the information to be evaluated. The information can be anything written: an original document; a transcript of a speech, conversation, discussion, or oral answer to a question; or a verbal description of visual information, such as a film, video, or photograph. Documents

18
Aug
Kinds of Data Required for Content Analysis

In the early stages of an assignment, evaluators choose variables of interest. For the descriptive Stars and Stripes assignment, for example, important variables included the frequency of stories on selected issues, such as the Iran-contra affair and the presidential campaign; the percentage of stories from other sources, such as staff reporters, AP, UPI, and

18
Aug
Kinds of Analysis Required in Content Analysis

Considering data requirements goes hand in hand with analysis requirements. In many evaluations, the most important, or only, form of analysis may be a simple aggregation of quantitative data or a comparison of categorical variables. When the subject matter is textual and the evaluation questions lend themselves to numerical descriptions or comparisons, content analysis

18
Aug
Resources Needed in Content Analysis

In content analysis, evaluators must consider three principal types of resources: an analyst with the technical knowledge and experience to plan and direct the content analysis, personnel to do the coding, and computer capability to carry out the analysis. At least one member of the project team should know about content analysis and have

18
Aug
Defining the Variables in Content Analysis

The assignment’s evaluation questions lead directly to the relevant variables. In the Stars and Stripes example, we asked “To what extent does the content of news stories in Stars and Stripes indicate management or censorship of the news management?” In practice, however, defining a variable may be separated into two parts: conceptualizing the variable

18
Aug
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