How to analyse your research data. Illustrations with hands-on exercises using SPSS

  • Keng Yin Loh
  • Cheong Lieng Teng
  • Kam Cheong Wong


Statistical analysis for a quantitative study is often perceived to be the most difficult step by a novice researcher. On the other hand, some researchers tend to over-analyse their research data in search of the illusive “significant” p-value. Some of these problems and pitfalls can be reduced if the researchers give some thoughts to their research objectives.

Another issue that trouble the novice is how much statistical knowledge one needs to have. There is no straight answer to this question; we feel that the information provided in this article is probably the bare minimum needed by most, if not all, researchers embarking on a research project. What about performing your own statistical analysis using statistical software? Although ability to handle statistical software is desirable, it is not mandatory as it is now possible to outsource to people who can do this properly. The researcher should, however, be able to tell the statistician what analysis is needed and to interpret statistical results. Take note that the statistician cannot undo the errors in the data (e.g. inadequate research design, inappropriate definition of research variables, inaccurate measurement during data collection, or data entry errors) – hence great care must be exercised during these earlier steps of research process. (copied from article)


Khoo EM. Research questions and research objectives. The Family Physician. 2005;13(3):25-26.

How to Cite
LohK. Y., TengC. L., & WongK. C. (2006). How to analyse your research data. Illustrations with hands-on exercises using SPSS. Malaysian Family Physician, 1(2 & 3), 5. Retrieved from
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