- #1

Conservation

- 63

- 0

- TL;DR Summary
- Nonparametric alternatives to unpaired t-tests given that the sample distributions are different

Hello everyone,

Say you have two sample distributions that are known to be two different distributions (one randomly drawn from a Poisson distribution, other randomly drawn from an uniform distribution). Given that you know the distributions are not going to be normal, a two-sample t-test would not be appropriate here. What are some non-parametric alternatives for comparing sample means in a scenario like this? I was thinking Mann-Whitney U test, but the Mann-Whitney test assumes that the two distributions are the same and measures shift. In this case, we would know that the two distributions are different.

Thanks!

Say you have two sample distributions that are known to be two different distributions (one randomly drawn from a Poisson distribution, other randomly drawn from an uniform distribution). Given that you know the distributions are not going to be normal, a two-sample t-test would not be appropriate here. What are some non-parametric alternatives for comparing sample means in a scenario like this? I was thinking Mann-Whitney U test, but the Mann-Whitney test assumes that the two distributions are the same and measures shift. In this case, we would know that the two distributions are different.

Thanks!