Madhu Bala, Indira Gandhi National Open University
Once you have selected the topic of the research and have gone through the process of literature survey, established your own focus of research, selected the research paradigm and methodology, prepared your own research plan and have collected the data; the next step is analysis of the data collected, before finally writing the research report.
Data analysis is an ongoing activity, which not only answers your question but also gives you the directions for future data collection. Data analysis procedures (DAP) help you to arrive at the data analysis. The uses of such procedures put your research project in perspective and assist you in testing the hypotheses with which you have started your research. Hence with the use of DAP, you can
Understanding of the data analysis procedures will help you to
The literature survey which you carried out guides you through the various data analysis methods that have been used in similar studies. Depending upon your research paradigm and methodology and the type of data collection, this also assists you in data analysis. Hence once you are aware of the fact that which particular procedure is relevant to your research project, you get the answers to:
There are numerous ways under which data analysis procedures are broadly defined. The following diagram makes it evident.
There are, in fact, a number of software packages available that facilitate data analysis. These include statistical packages like SPSS, SAS, and Microsoft Excel etc. Similarly tools like spreadsheets and word processing software are multipurpose and very useful for data analysis. The following links are useful for getting to know more about data analysis procedures and packages.
Multivariate Statistics: concepts, models, and applications by David W. Stockburger WWW Version 1.0 First Published July 1997 Revised March, 1998
Apart from data analysis procedures, there is another factor which is secondary analysis of qualitative data. For details of this method you can log on to http://www.soc.surrey.ac.uk/sru/SRU22.html by Janet Heaton
People generally believe in the universal notion that "one
can prove anything with statistics." This is only true
if we use data analysis procedures improperly. There are some
points that people often overlook while doing data analysis,
and also the way(s) people sometimes "bend the rules"
of statistics to support their viewpoint. The following website
discusses them very clearly. Taking examples from medicine,
education, and industry, it discusses the different ways in
which you can make sure that your own statistical procedures
are clear and accurate.
Pitfalls of Data Analysis (or How to Avoid Lies and Damned Lies) by Clay Helberg, M.S., Research Design and Statistics Unit
For further study on this area, you may log on to: Module 9 ‘Quantitative Analysis’ and Module 10 ‘Qualitative Analysis’ of MMU materials and Module 11 ‘Data Analysis and Modes of Analysis’ in the CQU materials.This module is available in our online resource. This resource is available to participants registered on the MA in Academic Practice only. If you are already registered, click here to go to the site. You'll need your username and password to login.
Dr Madhu Bala