QUALITATIVE DATA ANALYSIS
We now need to analyse the data from our qualitative research study in order to make sense of it and to make accessible to the researcher (and people who read the report of the research) the large amount of rich textual data that has been generated.
Data analysis consists of:
the evidence obtained from the research.
All this is concerned with the organisation and the interpretation of information (other than numerical information, which is generally the preserve of quantitative research) in order to discover any important underlying patterns and trends.
Qualitative data analysis involves such processes as coding (open, axial, and selective), categorising and making sense of the essential meanings of the phenomenon.
As the researcher works/lives with the rich descriptive data, then common themes or essences begin to emerge.
This stage of analysis basically involves total immersion for as long as it is needed in order to ensure both a pure and a thorough description of the phenomenon.
All this is concerned with the organisation and the interpretation of information (other than numerical information, which is generally the preserve of quantitative research] in order to discover any important underlying patterns and trends.
However, each type of qualitative research requires slightly different methods of data analysis:
The constant comparative method
The constant comparative method is the process that we use in qualitative research in which any newly collected data is compared with previously collected data that was collected in an earlier study.
This is a continuous ongoing procedure, because theories are formed, enhanced, confirmed, or even discounted as a result of any new data that emerges from the study.
A way in which data can be constantly compared throughout a research study is by means of coding:
open coding - open coding is the first organisation of the data to try to make some sense of it
axial coding - axial coding is a way of interconnecting the categories
selective coding - selective coding is the building of a story that connects the categories
At the end of these processes, it is hoped that one has achieved the production of a set of theoretical propositions (i.e. a theory to explain both the data and what is actually happening).
Qualitative data analysis is the process in which we move from the raw data that have been collected as part of the research study and use it to provide explanations, understanding and interpretation of the phenomena, people and situations which we are studying.
The aim of analysing qualitative data is to examine the meaningful and symbolic content of that which is found within. What we are aiming for is to try to identify and understand such concepts, situations and ideas as:
A personís interpretation of the world/situation in which they find themselves at any given moment.
How they come to have that point of view of their situation or environment in which they find themselves.
How they relate to others within their world.
How they cope within their world.
Their own view of their history and the history of others who share their own experiences and situations.
How they identify and see themselves and others who share their own experiences and situations.
It is important that before you decide upon your method of data analysis, you become very familiar and confident in your chosen field. The advice given throughout this web programme is to seek help and advice if you are not absolutely certain of what you should be doing, and this advice is reiterated here.
Having taken all that on board, now it is time to decide upon the method of data analysis that you are going to use in your own research proposal. This, of course, will in many ways be dictated by the methodology and data collection methods that you have already decided upon.
Click on the icon below to look at the data analysis that is described in the research proposal example we are using as a guide.