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1. Starting your Data Analysis
Most students get quite excited when they finish entering data and they have a data file to analyse. However, before diving in to address all your research questions there are a few things you need to do first. I have listed these below, along with the related chapter in the SPSS Survival Manual (A book every SPSS user must have. For more information visit http://www.allenandunwin.com )
- Check the characteristics of the subjects that make up your sample. You will need this information for the method section of your report.
- Check all the variables in your data file for errors (particularly out-of-range values).
- Obtain descriptive statistics for each of the variables you will be using in your study. These should include means, standard deviations, kurtosis, skewness, and minimum and maximum values.
- Check that these values are appropriate.
- Check the distribution of scores on each of your variables—depending on the variable, you will need to use histograms, boxplots, bar graphs or stem and leaf plots. Look out for very skewed distributions or any unusual pattern of scores. Also check for extreme outliers—these can affect some analyses and may need to be recoded or removed.
- Perform the necessary data manipulation procedures (e.g., recode, compute) to create any new variables you need. This is important when creating total scores on a scale, or collapsing down a variable into a smaller number of categories. Afterwards, always run Frequencies on these new variables to check that the procedure has been done correctly.
- Check the reliability of the scales you intend using in your analyses. What are the Cronbach alpha values for each scale? How do these results compare to those reported in the literature?
- For your continuous variables, check the pattern of inter-correlations. How strongly and in which direction are your variables related? How does this compare with the results reported in the literature? You may also need to obtain scatterplots of the correlation between pairs of your major variables. These are useful for checking for linear relationships between variables.
- When choosing which statistical technique to use for your analysis, always check that you have the right type of variables (categorical/continuous). Consider whether a parametric or a non-parametric technique is the most appropriate.
- Check with your statistics books and the SPSS Survival Manual to ensure you are not violating any of the major assumptions for the analyses you intend to conduct. This might involve checking that you have enough subjects in your groups, that the variance for each group is similar, or that the distribution of scores on your variables is not too skewed.
- Remember that SPSS will conduct the analyses that you ask it to do, whether or not these analyses are appropriate. The old saying ‘Garbage in, garbage out’ applies. It is up to you to ensure that you understand what you are doing and also what the output means.
A few additional tips
- Save your output regularly so that if the computer crashes you have not lost too much work. All output files should be saved with a .spo extension onto your disk in the A:/ drive. Give your output file a suitable name so you will able to identify it later, for example 8aug96a.spo. Keep a list of your output files with details of what is included. SPSS produces a lot of output and it is very easy to get lost, so get organised—it will save you a lot of time.
- If you need to recode a variable, always create a new variable. Keep the original variable so that if there are any problems you have not lost the data.
- If you create any new variables, always check in your codebook that the name you intend to use has not already been used. Otherwise you will lose all the original information. Record the name and explanation of the new variable in your codebook. Keep detailed notes of everything you do. This should include details of cut-off points you use to recode variables, reasons for doing things, reminders to yourself about how to do the analyses, problems that might have occurred etc.
- Finally, make sure that when doing your analyses, you get up and stretch, walk around etc., at least every hour. SPSS for Windows can be addictive, a bit like eating peanuts—just one more, and then, just one more … Plan what analyses you intend to do, break your analyses into blocks, and give yourself time to digest the output.
2. Preparing a research report
Once you have completed your data analysis, the next step is to write your research report. The format that you use to do this will vary according to the purpose of the report (lab report, thesis, journal article), and the discipline in which you are studying. Different disciplines (e.g., psychology, education, medicine, business) have different conventions for presenting reports, so you should consult your lecturer or supervisor for the specific requirements of your report. Many disciplines follow the guidelines laid down by the American Psychological Association (often referred to as APA style).
How to present your paper in correct APA style.
Sample report (APA Style)
You will need Adobe Acrobat Reader to read the Sample Report and ApA Style
3. Additional reading
There are many good statistics books that can be used to extend your understanding of the techniques covered in the SPSS Survival Manual. I have listed a few titles here to get you started. Watch out for new editions of these books as they appear.
- Bowling, A. (1997). Research methods in health: investigating health and health services. Buckingham: Open University Press.
- Boyce, J. (2003). Market research in practice. Boston: McGraw Hill.
- Cone, J. & Foster, S. (1993). Dissertations and theses from start to finish. Washington: American Psychological Association.
- Goodwin, C. J. (1998). Research in psychology: Methods and design (2nd edition). New York: John Wiley.
- Stangor, C. (1998). Research methods for the behavioral sciences. Boston: Houghton Mifflin.
- Oppenheim, A. N. (1992). Questionnaire design, interviewing and attitude measurement. London: St Martins Press.
Scale selection and construction
- Dawis, R. V. (1987). Scale construction. Journal of Counseling Psychology, 34, 481 489.
- DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Thousand Oaks, California: Sage.
- Gable, R. K. & Wolf, M. B. (1993). Instrument development in the affective domain: Measuring attitudes and values in corporate and school settings. Boston: Kluner Academic.
- Kline, P. (1986). A handbook of test construction. New York: Methuen.
- Robinson, J.P. Shaver, P. R. & Wrightsman, L. S. (Eds.), Measures of personality and social psychological attitudes. Hillsdale, NJ: Academic Press.
- Streiner, D. L. & Norman, G. R. (1995). Health measurement scales: A practical guide to their development and use (2nd edition). Oxford: Oxford University Press.
- Cooper, D. R., & Schindler, P. S. (2003). Business research methods (8th ed.). Boston: McGraw Hill.
- Everitt, B. S. (1996). Making sense of statistics in psychology: A second level course. Oxford: Oxford University Press.
- Gravetter, F. J. & Wallnau, L. B. (2000). Statistics for the behavioral sciences (5th edition). Belmont, CA: Wadsworth.
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