I have this matrix:
x <- c(2, 38, 196, 2) contingency <- matrix(x, nrow = 2, byrow = TRUE) print(contingency) [,1] [,2] [1,] 2 38 [2,] 196 2
And I've carried out this Fisher's Exact Test:
which outputs this:
Fisher's Exact Test for Count Data data: contingency p-value < 2.2e-16 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 6.103516e-05 4.703333e-03 sample estimates: odds ratio 0.000701445
My questions are:
The values in the matrix (2, 38, 196, 2) are means. Is it ok to run a Fisher’s Exact Test on these data?
If I was to conclude that the proportions in each group are unlikely to be equal, would i be correct?