Originally Posted by

**mmercker**
Hi Diana,

I think a t-test ist perfect in both cases. However, you have to check the assumptions for a parametric T-test, which are: (1) normality of the data for each sample (e.g., via Shapiro-Wilk test or QQ-plots), and (2) variances are the same (e.g., via Levene's test or graphically). However, since you have huge samples, I would recommend to test these assumptions graphically, since Shapiro-Wilk-test and Levene's test can be significant even if violations of homogeneity or normality are pretty small and actually could be neglected. This is because with huge samples these tests have pretty much statistical power.

If both assumptions are met, perform a students T-test. If only homogeneity of variance is violated, you can perform a Welch's T-test. If normality is violated, you can perform a non-parametric T-test, such as the U-test or a permutation T-Test