Qualitative Data Analysis
Qualitative data analysis What Is Qualitative Analysis?
Qualitative modes of data analysis provide ways of discerning, examining, comparing and contrasting, and interpreting meaningful patterns or themes.
The varieties of approaches - including ethnography, narrative analysis, discourse analysis, and textual analysis - correspond to different types of data, disciplinary traditions, objectives, and philosophical orientations.
What Is Qualitative Analysis?
We have few agreed-on canons for qualitative data analysis, in the sense of shared ground rules for drawing conclusions and verifying their sturdiness
(Miles and Huberman, 1984).
Data analysis tends to be an ongoing and iterative (nonlinear) process in qualitative research.
The term we use to describe this process is interim analysis (i.e., the cyclical process of collecting and analyzing data during a single research study). Interim analysis continues until the process or topic the researcher is interested in is understood (or until you run out of resources!). Throughout the entire process of qualitative data analysis it is a good idea to engage in memoing (i.e., recording reflective notes about what you are learning from the data).
The idea is to write memos to yourself when you have ideas and insights and to include those memos as additional data to be analyzed.
Throughout the course of qualitative analysis, the analyst should be asking and reasking the following questions:
What patterns and common themes emerge in responses dealing with specific items? How do these patterns (or lack thereof) help to illuminate the broader study question(s)?
Are there any deviations from these patterns? If yes, are there any factors that might explain these atypical responses?
What interesting stories emerge from the responses? How can these stories help to illuminate the broader study question(s)?
Do any of these patterns or findings suggest that additional data may need to be collected? Do any of
Qualitative modes of data analysis provide ways of discerning, examining, comparing and contrasting, and interpreting meaningful patterns or themes.
The varieties of approaches - including ethnography, narrative analysis, discourse analysis, and textual analysis - correspond to different types of data, disciplinary traditions, objectives, and philosophical orientations.
What Is Qualitative Analysis?
We have few agreed-on canons for qualitative data analysis, in the sense of shared ground rules for drawing conclusions and verifying their sturdiness
(Miles and Huberman, 1984).
Data analysis tends to be an ongoing and iterative (nonlinear) process in qualitative research.
The term we use to describe this process is interim analysis (i.e., the cyclical process of collecting and analyzing data during a single research study). Interim analysis continues until the process or topic the researcher is interested in is understood (or until you run out of resources!). Throughout the entire process of qualitative data analysis it is a good idea to engage in memoing (i.e., recording reflective notes about what you are learning from the data).
The idea is to write memos to yourself when you have ideas and insights and to include those memos as additional data to be analyzed.
Throughout the course of qualitative analysis, the analyst should be asking and reasking the following questions:
What patterns and common themes emerge in responses dealing with specific items? How do these patterns (or lack thereof) help to illuminate the broader study question(s)?
Are there any deviations from these patterns? If yes, are there any factors that might explain these atypical responses?
What interesting stories emerge from the responses? How can these stories help to illuminate the broader study question(s)?
Do any of these patterns or findings suggest that additional data may need to be collected? Do any of