I'm working on a research project, and I could use a little assistance in picking the correct test.
There are two cohorts that took a pre-test. Subsequently, the intervention group was given a lecture on the subject while the control group did self-study. Both groups then took the identical post-test.
My current thought was that I could compare the mean change (delta) in scores for each cohort and use a T-test. We have a very small sample size: only 20. For that reason, I was thinking that a non-parametric test may be useful. I have read about Wilcoxon Rank Sum test, but I have a few questions.
1.) Is that the correct test to use?
2.) In JMP, the software I'm using, they have multiple ways to run Wilcoxon Rank Sum tests, and I can't figure out which way to do it.
a. Analyze-->Fit Y by X-->Delta Score by Cohort-->Nonparametric-->Wilxocon.
--This method gives me "2 sample test, normal approximation" and "1 way test, chiSquare approximation". Which should I be using and why?
b. I also saw that you can do a Wilcoxon "test of the mean" when using Analysis-->Distribution-->DeltaScore. I'm assuming that is just to prove that the delta is significantly different from 0. That didn't seem like the correct test to show that interventions improved more than controls. Am I interpreting that correctly?
Thank you all so much in advance for all of your help!!