Data Analysis

Data Analysis

Data analysis is an integral part of qualitative research and constitutes an essential stepping-stone toward both gathering data and linking one’s findings with higher order concepts. There are many variants of qualitative research involving many forms of data analysis, including interview transcripts, field notes, conversational analysis, and visual data, whether photographs, film, or observations of internet occurrences (for the purpose of brevity, this entry calls all of these forms of data text).

First, the gathering of data and the analysis of those data are iterative processes. In its ideal form, early data analysis provides sufficient insight to shape the gathering of further data.

Researchers who conduct interviews may use early analysis to revise interview guides or to focus future interviews. Some field-workers do not settle on a research question until they have spent some time in the field and have observed and begun to analyze what is of theoretical interest in a particular social setting.

Both during and after collecting data, researchers engage in memoing. Memoing occurs when researchers take note of personal, conceptual, or theoretical ideas or reflections that come to mind as they collect and analyze the data. Early memoing may occur while researchers are writing up field notes or transcribing interviews.

Some researchers find it useful to embed memos into their actual field notes or interview transcripts, whereas others find it more profitable to set up the memos separately. No doubt there are researchers who combine the two methods. Some researchers use memos themselves as material for coding, as described next.

Any analysis of data involves some form of coding. Coding reflects both the personal analytic habits of researchers and the general principles that flow from particular qualitative research methodologies and theoretical perspectives. In its most stringent form, the analysis of data can entail line-by-line coding of text whereby researchers capture every empirical and conceptual occurrence in each line.

Qualitative researchers arrive at a more profound analysis of the data when they engage in writing up the data as soon as possible. These short or lengthy writing bouts often yield insights that were not readily apparent even after the coding had been completed. Indeed, researchers may find that they need to go back to the data to recode for concepts that became apparent during the initial writing up of the data.

All data analysis must move toward developing concepts or relating to already existing concepts. This final stage of data analysis is analogous to having a conversation with the literature of the discipline or what was found in other social settings.

More recently, researchers have seen the introduction of software, such as Ethnograph and NVivo, developed for the express purpose of managing and coding qualitative data. These programs, however, remain controversial and have influenced, and continue to influence, data analysis in unforeseen ways.