Question about unequal sample size for testing for normality Let's say I have two variables I want to run correlation between (variables A and B). I have measures of each variable for the same 25 subjects. On top of that for variable B, I have data for an extra 10 subjects (so for variable A, n = 25, and for variable B, n = 35). So when I run the correlation analysis, I'll be including the 25 subjects in common for each variable. Before running correlation I want to test normality assumption for each variable. My question is: when I test the assumption for variable B, do I include in the test the full 35 subjects or only the 25 I plan to include in the correlation analysis?
Thanks,
FBH

I can see arguments for each.
25 is the easy one to argue. You are calculating the correlation using only those $25$ points. Who cares what wacky behavior those other points have? They are not part of the analysis.
35 also can be defended. If you believe all $35$ points come from the same population (likely due to your knowledge of the experiment), you can tighten up your analysis by using the larger sample size. If you run a formal hypothesis test, you will have greater power to reject a false null hypothesis.
