So I have the following in R:
A=c(0,0,4,0,0,0,0,0,3,3,0,0,0,0,0,0,0,0,10,0,0) B=c(5,0,53,1,18,9,50,2,67,27,4,5,3,0,38,0,3,1,94,0,0) tab=as.table(rbind(A,B)) row.names(tab)=c('responders','non_responders') fisher.test(tab, workspace = 2e8)
Basically it is a measurement of 21 variables of A & B. I don't really understand the fisher.test documentation on the R website, but with the way that I ran it, is it really telling me the difference between A & B distribution of variables?
If there is an alternative appropriate statistical test that will tell me if there is a difference between A & B distributions of measured variables then please let me know as well.
There is a good reason to keep the instances where there are zeros in the same column in the table as well. This is just a single dataset. I have approximately 300 like this where there is a measurement in each column at least once. And the goal is find which of the 300 are statistically different.