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PhD Thesis Writing Tips: Mind Your Data

So, you have identified the area of interest for your PHD thesis, and you have completed a great literature search. You know your work may be published and that future employers will want to talk about your thesis and they may want to see it and actually read it.

But, before you get to that point you still have a more planning and writing to do. You have identified the data needed, how to collect it, what exactly it is going to prove and how to analyse it.

Data and its treatment needs careful handling, as a rough guide the following checklist may be helpful:

  1. Check that the data you are using is actually want you need to support your work.
  2. Is the methodology correct for the data you need to produce? Check the conditions under which the data was produced.

  3. Were the results constant? Re-check this.
  4. Is there any other relevant information the reader needs in order to make sense of the results. Remember that you should not assume that the reader (examiner) will automatically draw inferences from your data, its your job to guide them through the data and the results. Typically if it is not written in your work - it does not exist!

  5. Make sure that the correct statistical tests are used - don’t use a Mann-Whitney test when you really need an ANOVA, as it will completed throw out all or the results and any conclusion you may decide on.
  6. Use graphs to report the results and also to provide an illustration of the results. When using graphs show standard errors etc.

Very Important

This may sound very basic but, get someone to check and recheck your data. It has been known that a miscalculation or an error in interpreting data has resulted in rejecting the hypothesis, when in fact the data supported the hypothesis. A simple error at this point can be catastrophic. Admittedly sometimes data produced can genuinely be a surprise and not support the projected outcome.

The best advice at any level of study, when using data is:

Check, check again and re-check.

Make sure that the data you are producing actually meets you needs.

Check again.

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