I have 2 groups of data to compare using a t-test, both of sample size n=5. Checking to see if the normality assumption of the test holds is difficult since the sample sizes are too small.
I have read that a t-test is robust to non-normality in this case since the sample sizes are equal. However if the data were highly non-normal it might no longer be robust. An alternative would be to perform an Mann-Whitney U test but this test has less power than the t-test (though I'm not sure how less). I actually encounter situations similar to these all of the time and realise there may not be a definitive answer but I am just curious how others in the community would approach this sort of problem. I typically just go with the t-test and tell others to do the same since they are more familiar with the test than the MW test.