Introduction

Data analysis is probably the aspect of qualitative research that most clearly distinguishes it from quantitative research. Qualitative data analysis is primarily an inductive process of organizing the data into categories and identifying patterns (relationships) among the categories. Unlike quantitative procedures, most categories and patterns emerge from the data, rather than being imposed on the data prior to data collection.

This session will focus on data analysis related to primarily ethnographic research. That is, we assume that data are collected from participant observation, ethnographic interview, and documents.

Q.S.R.'s Introduction to Qualitative Analysis

Process of Qualitative Data Analysis

Data analysis is an ongoing cyclical process integrated into all phases of qualitative research. It is an inductive process in which categories and patterns emerge from the data rather than being imposed on data prior to data collection.

Qualitative data analysis usually undergoes the following stages:

Source: McMillan and Schumacher (1997, p. 503)

Categorizing Strategies

1. Coding topics
2. Classifying topics
3. Developing topics as categories (emic and etic categories)
4. Seeking patterns

Exercise (1): Brainstorming as many topics related to a theme as possible, and develop a pattern out of the topics.

Exercise (2): Coding topics, classifying topics, developing categories, and seeking patterns. (Source: McMillan and Schumacher (1997, p. 537)

Contextualizing Strategies

Contextulizing strategies operate quite differently from categorizing ones. Instead of fracturing the initial text into discrete elements and re-sorting it into categories, contextulizing analysis attempts to understand the data in context to identify the relationships among the different elements of the text. Contextulizing strategies do not focus on relationships of similarity that can be used to sort data into categories independently of context but instead look for relationships that connect statements and events within a context into a coherent whole.

Case analysis (Maxwell, 1996).

Computer-Assisted Qualitative Data Management and Analysis

Computer can assist qualitative data management and analysis in many ways:

• Making notes in the field
• Writing up or transcribing field notes and interview data
• Editing--correcting and elaborating field notes and interview transcriptions
• Coding--placing keywords or symbols to segments of data to permit later retrieval
• Filing--keeping data in an organized database
• Search and retrieval -- locating relevant segments and chunks of data and making them available for examination
• Data "linking"--connecting relevant data segments with each other, forming categories and patterns for closer examination
• Memoing--writing reflective commentaries on some aspect of the data as a basis of deeper analysis
• Content analysis -- frequencies, sequence, or locations of words and phrases
• Display -- placing selected data in a condensed, organized format such as a matrix or network for examination
• Graphic mapping -- creating diagrams that depict findings or theories
• Preparing interim, drafts, and final reports

Sample computer program analysis :QSR NUD.IST.

Comparison of qualitative data analysis software packages by Carl Cuneo

Reporting Qualitative Data Analysis Results

• Descriptive narration
• Topology
• Theme analysis and interpretation
• Grounded theory

References

1. Maxwell, J. A. (1996). Qualitative research design: An interactive approach. Newbury, CA: Sage.
2. McMillan, J. H., & Schumacher, S. S. (1997). Research in education: A conceptual introduction. New York: Longman.