Online Research Methods Resource

Data Analysis Procedures

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

  • convert data into information and knowledge, and
  • explore the relationship between variables.

Understanding of the data analysis procedures will help you to

  • appreciate the meaning of the scientific method, hypotheses testing and statistical significance in relation to research questions
  • realise the importance of good research design when investigating research questions
  • have knowledge of a range of inferential statistics and their applicability and limitations in the context of your research
  • be able to devise, implement and report accurately a small quantitative research project
  • be capable of identifying the data analysis procedures relevant to your research project
  • show an understanding of the strengths and limitations of the selected quantitative and/or qualitative research project
  • demonstrate the ability to use word processing, project planning and statistical computer packages in the context of a quantitative research project and report
  • be adept of working effectively alone or with others to solve a research question/ problem quantitatively.

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:

  • What kinds of data analysis tools are identified for similar research investigations? and
  • What data analysis procedures should you use for your purpose?

There are numerous ways under which data analysis procedures are broadly defined. The following diagram makes it evident.

diagram of data analysis procedures

 

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

PSY2005 Statistics and Research Methods: Quantitative data analysis component

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.

 

June 2005

photo of Madhu Bala

Dr Madhu Bala

Room No.112, Faculty of Economics,
School of Social Sciences, Block-F,
Indira Gandhi National Open University,
Maidan Garhi, New Delhi, India- 110068
E-mail: mbala@ignou.ac.in, madhu81@hotmail.com

 

The materials have been produced by IGNOU and MMU with additional support from the British Council and the Central Queensland University.