For independent reasons, I'm working on two bootstrapped datasets, A and B, of the same size, each consisting of a 1000 samples. To compare the distributions of A and B, I ran a Fischer F-test on pairs of boostrapped samples from the two datasets to test the null hypothesis that the variances are homogeneous. I found that, across 1000 pairs of A and B samples, the null hypothesis was rejected 87.1% at p<0.05.
As is customary when performing the F-test, I would like to report the F-statistic, the degrees of freedom, and the p-value. However, given that I have a 1000 sets of these values, it is not feasible to report them all. In this case, it is reasonable to report the average F-statistic and p-value across the 1000 comparisons? The degrees of freedom should stay the same.
If reporting average statistics is not appropriate, then what would be a good alternative?