You have successfully defended your dissertation proposal, and now you have your dissertation data. It might seem like the next logical step would be to run your analysis according to the analysis plan from your proposal.

However, it is important to make sure that the statistics test you plan to run is appropriate for the data that you obtained. Sticking to a rigid plan for which statistics test to use that you made before you obtained your data can be very dangerous in terms of the validity of your entire project, because that plan may no longer apply to your data, especially if your hypothesis is very different from what you found.

Some common issues with statistical procedures that you should consider include limited number of participants, limited number of cases across groups, and violations of normality of key variables. To test for these issues, you will want to work closely with your advisor or a statistical consultant and examine the data to determine if the statistics test you want to use is still appropriate. Once you have a sense of the data, you can make a more informed decision about how to proceed with the analysis.

If you happen to find violations of certain assumptions, there is no need for panic or despair; you can always adjust which statistics test to use to meet the needs of the data. For example, if the data violate the assumption of normality, non-parametric alternatives might be an appropriate alternative to your original analysis plan. If you do have to make any alterations to your analysis plan between creating your proposal and running the analysis, you will want to work closely with your advisor and your committee to make sure that you are on the right track and see your work from the perspective of someone else.



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