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How to interpret & write up results

Woo! We can now perform the tests; however, this isn’t very useful if we cannot interpret what they tell us!

To report our results, we need to:

  • Report the p value
  • Is the p value significant or not?

If it is significant

  • Report our Cramer’s V value
  • What strength is this? (Use the guide below to interpret)
  • Describe some notable comparisons from our observed and expected count tables

Cramer’s V Interpretation Guide

Zero – No association between variables 

0.2 – Weak association between the variables

0.4 – Medium association between variables 

0.6 – Strong association between variables 

0.8 – Strange (possible but check calculations) 

1 – Variables are perfectly associated

What about the results from the previous sprint?

Revisit the previous sprint and jot down the above criteria.


Using the dataset we have been working on, choose your own 2 variables to run a Chi-Square and Cramer’s V test on.

Do you have any cells with an expected count less than 5? If so, what do we do with this?

  • What is your p value? Sig or not?
  • Strength of the Cramer’s V if applicable