group 1: treatment A

group 2: treatment B

thickness of the skin was compared between group 1 (n=20) and group 2 (n=20)

I have used a non-parametric Mann-Whitney test resulting in a highly significant difference.

Now, the reviewer of my paper has rejected the submission with the following arguments:

"Why was the non-parametric Mann-Whitney test used? The data is numerical in nature. The sample size was reasonable. An unpaired two-tail t-test would seem the logical choice, unless there was a specific reason not to perform this test. Is the data normally distributed? This can be tested using a D'Agostino- Pearson normality test. Please present statistics as parametric (t-test) unless you can specifically explain why you are using a non-parametric test on this data. If it is because it does not obey normal distribution then present data qualifying this."

For me it is absolutely not clear why it should not be allowed to use a non-parametric statistic test. Even if data are normally distributed and with comparable variance, a non-parametric test would be allowed. If they are not normally distributed, a non-parametric test would also be the best. Can anyone explain to me if I am wrong and the reviewer is right - and if I really have to use an independent student t-test in such a situation.

Thank you a lot for your help

Chris