Data analysis in qualitative research, as contrasted with quantitative research, is generally

According to Richard C. Rich and colleagues (2018) In most cases, qualitative or quantitative data is used in scientific study. Both sorts of data can be beneficial, and any given study may include both. However, collecting the two sorts of data necessitates two distinct research strategies.

Quantitative methods emphasize detached observation and documenting phenomena numerically.

Qualitative methods, on the other hand, study social phenomena in their entirety, in the context in which they occur, while considering the meanings that those being studied give to their actions and to the actions of others. Qualitative research “entails immersion [of the researcher] in the everyday life of the setting chosen for study, values and seeks to discover participants’ perspectives on their worlds, views inquiry as an interactive process between the researcher and the participants, is both descriptive and analytic, and relies on people’s words and observable behavior as the primary data” (Marshall and Rossman 1999, 7).

Qualitative research is less likely than quantitative work to be interested in testing theories constructed in advance. Qualitative research attempts to gain insights into some phenomenon while developing a conceptual understanding. Thus, qualitative theories are often constructed as observations are made.

In contrast to quantitative theories postulated in advance, the qualitative process may produce theories that are more firmly grounded in reality. However, this practice may open the door to unintentionally shaping a theory to fit observations, leading to an untestable theory. Critics of qualitative work contend that such “theories” apply only to the cases actually observed and, as a result, are of limited usefulness.

The key point to remember is that empirical research can be either quantitative or qualitative so long as its purpose is to characterize real-world phenomena rather than to assess them in a normative context. The following section compares qualitative and quantitative methods. It is important to recognize that the distinctions discussed are generally more matters of degree than absolutes; the two types of methods often require different forms of work, but are working toward similar objectives.

• Research Methods and Research Designs 

Whether doing qualitative or quantitative research, you need to be clear about your research question and what you seek to learn from your study. Quantitative research tries to establish cause-and-effect relationships, whereas qualitative studies are more concerned with describing people or events as they “naturally” occur. Thus, qualitative research is far less likely to emphasize research designs that allow researchers to “hold constant” some factors in order to make causal inferences. A qualitative research design will generally focus on who or what is to be observed, in what settings they are to be observed, how observations are to be conducted, and how data (often referred to in qualitative research simply as “information”) will be recorded.

By contrast quantitative research will require a design that produces standardized data about a representative (or at least typical) set of cases (people, events, documents, institutions, etc.) and does so in a way that would allow another researcher to obtain the same results. The emphasis is on obtaining accurate and objective measurement of variables among a set of cases. This usually involves conceptually isolating a variety of features of each case for measurement. Critics of the approach feel that meaning, or significance, is lost in this process and argue for a more holistic approach. Quantitative researchers, however, feel that what is lost in context is more than offset by increases in the ability to precisely compare cases that quantitative methods of data collection offer.

• Differences in Sampling

 Whereas quantitative research is concerned with generalizing conclusions to large populations, qualitative work is more concerned with gaining insights into specific cases from which they can construct a detailed understanding of broad phenomena. In quantitative research, sampling is often based on the logic of probability and designed to produce statistical representativeness. It is usually done in advance of data collection. By contrast, the sample for a qualitative study often emerges as the study progresses. That is, researchers will select an initial case to observe and then let what they learn from those observations determine whom or what they observe next. This strategy reflects the belief that we can determine where to look for the answers we seek only after gaining a partial understanding of the subject by direct experience with it. This is consistent with qualitative researchers’ view that each case is unique and should not be treated in a standardized way (as is done in quantitative research).

Qualitative researchers are also often far less concerned with observing “representative” cases than with observing cases that will yield the insights they seek. To illustrate, a quantitatively oriented scholar might try to understand the fundamental assumptions that constitute a “political culture” by surveying a representative sample of “ordinary” citizens. By contrast, a qualitative researcher might conduct in-depth interviews with several people who reject the dominant political culture. By understanding the political thought of these “outsiders,” the qualitative researcher hopes to see how accepting the prevailing political culture influences the majority’s thinking about politics by seeing how those who do not accept it differ from those who do.

• Differences in Data Collection

 Some of the most dramatic differences between qualitative and quantitative methods appear in the data collection stage. Data in qualitative research usually consist of words (or sounds and images translated into words) rather than numbers (or words or images translated into numbers), as they do in quantitative research.

This underlying difference in form of data influences the means of collection. Whereas a quantitative researcher typically spends little time with each subject, qualitative researchers’ data collection usually involves extended observation of (or even participation in) the phenomenon under study and extensive interaction with subjects. Rather than standing apart from the people or events to be studied, the qualitative researcher is often intimately engaged with them. In this way researchers can probe for the information they need to understand why people act as they do, or what impact some specific event had on those who experienced it.

You may recall the concerns over reactivity raised by the discussion of the Hawthorne effect and wonder how qualitative researchers deal with this because they are so involved with those being studied. First, qualitative researchers may conceal the observer or the purpose of the research from the subjects. Second, many qualitative researchers depend not on deception or concealment, but on gaining trust and their own perceptiveness to avoid artificial reactions while being fully honest about their purposes.

The goal of qualitative research is for the researcher to build a strong enough relationship with those being observed that they will reveal their true feelings and will act “naturally” because they feel that the researcher will not judge or harm them. At a minimum, the researcher will learn enough about the subjects and their context to know when they are not being truthful or are modifying their behavior because of the researcher’s presence.

• Differences in Data Analysis

 The distinction between the data collection and data analysis phases of research is far less clear for qualitative studies than for quantitative ones. In quantitative studies, data analysis is planned in advance so that data can be obtained in the necessary form. The analysis is then carried out after all the data are gathered. In studies using qualitative methods, data collection and analysis generally proceed together. Because data collection in qualitative research consists primarily of observing and recording those observations, the very act of deciding what to pay attention to and how to record it involves some analysis.

To illustrate, consider a qualitative researcher who seeks to understand the political power structure in a voluntary organization by observing its meetings. This observer will see, hear, and feel a great deal at each meeting—the temperature in the room, noises from outside, whether or not people bring small children to the meeting—but may regard most of it as irrelevant to the research. However, some seemingly irrelevant things may be important in understanding the power structure.

Deciding whether to record and how to describe such things as what types of clothes different people wear to the meeting, the order in which they arrive, or the tone of voice they use in asking questions involves deciding what each of these things means in the context of the study. That requires analysis on the spot in order to decide what to attend to and more analysis when writing up the notes later in deciding what to record.

Failing to recognize the importance of an event when it is observed or transcribed can lead to a failure to understand accurately the subject under study. Thus, some analysis must begin immediately. As a result, qualitative researchers often modify their data collection techniques in the course of the project as a result of new insights gained from this early analysis.

Another distinction between qualitative and quantitative research is the use of computerized data analysis. With large numeric data sets, statistical software is central to most quantitative analysis. Qualitative researchers are far less likely to make much or any use of software packages because the form of data they have (narratives) does not lend itself to computerized manipulation. A number of computer programs have been developed to assist in the analysis of qualitative data, so this distinction is not absolute. However, it is highly unlikely that computerized analyses will ever be used as extensively in the interpretation of qualitative data as they are in quantitative research.

• Different Standards of Evidence

 Quantitative researchers are usually able to employ some well-established rules of analysis in deciding what is valid evidence for or against their theory. These include such tools as measures of statistical significance, statistical tests of validity, and formal logic.

Qualitative researchers generally lack this type of commonly agreed-to “objective” tool. Rather, they must rely on their ability to present a clear and full description, offer a compelling analysis, and make a convincing argument for their interpretation to establish the value of their conclusions.

Advocates of qualitative methods argue that this is because they seek to deal with the richness of complex realities rather than abstracting artificially constructed pieces of those realities for quantitative analysis. Critics of their approach contend that the vagueness and situational nature of their standards of evidence make it difficult (if not impossible) to achieve scientific consensus and, therefore, to make progress through the accumulation of knowledge.

• Differences in Reporting the Results

 Reports of quantitative research usually rely heavily on presentations of numerical data in the form of tables or charts. Direct and detailed presentation of these data are necessary to make the case for the quantitative interpretations being offered. In contrast, reports of qualitative projects often include long quotations from the people being studied or present the “stories” they told the researcher about their “lived experience.” This is necessary not only to capture the full complexity of the subject matter, but also to give readers a way to judge the validity of the researcher’s interpretations (as explained in the discussion of rules of evidence earlier). Qualitative researchers must very carefully document their methods and processes as they decide what evidence (quotations, observations, etc.) to include in order to allow readers a chance to evaluate the conclusions critically.

Conclusion

The goal of reviewing some of the key differences between qualitative and quantitative methods is to convince you to be open to using the most appropriate method(s) for your research question and theory as you construct your research design. Rather than facing a stark choice between two divergent methods, qualitative and quantitative methods are often best used as complements to one another in a single study, with the results from each approach providing a form of validation for findings generated from the other. You will be better able to make these judgments after finishing this text.

What is the data analysis of qualitative and quantitative research?

What is the contrast of quantitative data and qualitative data?

What is data analysis in qualitative research?

Why is the analysis of quantitative data different from that of qualitative data?