Qualitative versus quantitative research methods refers to data-oriented considerations about the type of data to collected and how they are analyzed. Qualitative research relies mostly on non-numeric data, such as interviews and observations to understand their meaning, in contrast to quantitative research which employs numeric data such as scores and metrics. Hence, qualitative research is not amenable to statistical procedures, but is coded using techniques like content analysis. Sometimes, coded qualitative data are tabulated quantitatively as frequencies of codes, but this data is not statistically analyzed.  Qualitative research has its roots in anthropology, sociology, psychology, linguistics, and semiotics, and has been available since the early 19th century, long before quantitative statistical techniques were employed.

Distinctions from Quantitative Research

In qualitative research, the role of the researcher receives critical attention.  In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and her specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a “neutral” or unbiased stance during the data collection and analysis processes, and ensure that her personal biases or preconceptions does not taint the nature of subjective inferences derived from qualitative research.

Analysis in qualitative research is holistic and contextual, rather than being reductionist and isolationist. Qualitative interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in qualitative research is viewed in terms of systematic and transparent approaches for data collection and analysis rather than statistical benchmarks for construct validity or significance testing.

Lastly, data collection and analysis can proceed simultaneously and iteratively in qualitative research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change her original research question if she realizes that her original research questions are unlikely to generate new or useful insights. This is a valuable but often understated benefit of qualitative research, and is not available in quantitative research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.

Benefits and Challenges of Qualitative Research

Qualitative research has several unique advantages. First, it is well-suited for exploring hidden reasons behind complex, interrelated, or multifaceted social processes, such as inter-firm relationships or inter-office politics, where quantitative evidence may be biased, inaccurate, or otherwise difficult to obtain. Second, it is often helpful for theory construction in areas with no or insufficient pre-existing theory. Third, qualitative research is also appropriate for studying context-specific, unique, or idiosyncratic events or processes. Fourth, it can help uncover interesting and relevant research questions and issues for follow-up research.

At the same time, qualitative research also has its own set of challenges. First, this type of research tends to be more time and resource intensive than quantitative research in data collection and analytic efforts. Too little data can lead to false or premature assumptions, while too much data may not be effectively processed by the researcher. Second, qualitative research requires well-trained researchers who are capable of seeing and interpreting complex social phenomenon from the perspectives of the embedded participants and reconciling the diverse perspectives of these participants, without injecting their personal biases or preconceptions into their inferences. Third, all participants or data sources may not be equally credible, unbiased, or knowledgeable about the phenomenon of interest, or may have undisclosed political agendas, which may lead to misleading or false impressions. Inadequate trust between participants and researcher may hinder full and honest self-representation by participants, and such trust building takes time. It is the job of the qualitative researcher to “see through the smoke” (hidden or biased agendas) and understand the true nature of the problem. Finally, given the heavily contextualized nature of inferences drawn from qualitative research, such inferences do not lend themselves well to replicability or generalizability.