I would like to investigate whether there are siginifcant differences between three different groups. There are about 20 numerical attributes for these groups. For each attribute there are about a thousand observations.
My first thought was to calculate a manova. Unfortunately, the data are not normally distributed (tested with Anderson Darling test). From just looking at the data, the distribution is too narrow around the mean and has no tail at all. When I calculate the Manova anyway, highly significant results come out that are completely against my expectations.
Therefore, I would like to calculate a multivariate Kurskall Wallis test next. So far I have found scipy.stats.kruskal. Unfortunately, it only compares individual data series with each other. Is there already a similar implementation in Python to a MANOVA, where you read in all attributes and all three groups and then give a result?
If you need more information, please let me know.
Thanks a lot! :)
