Approaches to Qualitative Data Analysis

Approaches to Qualitative Data Analysis

Written by Louis Cohen, Lawrence Manion and Keith Morrison in Research Methods in Education. New York: Routledge. 2007. pp 461-467.


I. Introduction
Qualitative data analysis involves organizing, accounting for and explaining the data; in short, making sense of data in terms of the participants’ definitions of the situation, noting patterns, themes, categories and regularities.



II. Setting Out
There is no one single or correct way to analyse and present qualitative data; how one does it should abide by the issue of fitness for purpose. Further, qualitative data analysis, as we shall see here, is often heavy on interpretation, and one has to note that there are frequently multiple interpretations to be made of qualitative data – that is their glory and their headache! In abiding by the principle of fitness for purpose, the researcher must be clear what he or she wants the data analysis to do as this will determine the kind of analysis that is undertaken. The researcher canset out, for example:
- to describe
- to portray
- to summarize
- to interpret
- to discover patterns
- to generate themes
- to understand individuals and idiographic features
- to understand groups and nomothetic features (e.g. frequencies, norms, patterns, ‘laws’)
- to raise issues
- to prove or demonstrate
- to explain and seek causality
- to explore
- to test
- to discover commonalities, differences and similarities
- to examine the application and operation of the same issues in different contexts.

The significance of deciding the purpose is that it will determine the kind of analysis performed on the data. This, in turn, will influence the way in which the analysis is written up. The data analysis will also be influenced by the kind of qualitative study that is being undertaken. The analysis will also be influenced by the number of data sets and people from whom data have been collected.

III. Ways of organizing and presenting Data Analysis
1. Organizing a qualitative data analysis – by groups. The advantage of this method is that it automatically groups the data and enables themes, patterns and similar to be seen at a glance.

2. A second way of organizing the data analysis is by individuals. Here the total responses of a single participant are presented, and then the analysis moves on to the next individual.

3. A third way of organizing data is to present all the data that are relevant to a particular issue.

4. A fourth method of organizing the analysis is by research question. This is a very useful way of organizing data, as it draws together all the relevant data for the exact issue of concern to the researcher, and preserves the coherence of the material.

5. A fifth method of organizing the data is by instrument. Typically this approach is often used in conjunction with another approach, e.g. by issue or by people.

IV. Methodological tools for analysing qualitative data
1. Analytic induction, that is to deliberate opposition to statistical methods of data analysis.
2. Constant comparison. In constant comparison the researcher compares newly acquired data with existing data and categories and theories that have been devised and which are emerging, in order to achieve a perfect fit between these and the data.
3. Typological analysis.Typological analysis is essentially a classificatory process wherein data are put into groups, subsets or categories on the basis of some clear criterion (e.g. acts, behaviour, meanings, nature of participation, relationships, settings, activities).
4. Enumeration. The process of enumeration is one in which categories and the frequencies of codes, units of analysis, terms, words or ideas are counted.