I want to compare the variance of two "different" data sets for hypothesis
testing.  If I assume the distributions of both data sets were normal, then
I simply apply the F-test.  But I do not want to assume that the
distributions were derived from normal populations.

I've searched and searched, but can't seem to find a clear explanation of
what is the appropriate replacement test (for the F test) for two non-normal
distributions.  Can anyone help?  Why is there so much discussion about
U-MannWhitney and other non-parametric tests that seem to focus more on
T-test replacements.  At least that is what it seems like from my limited
perspective.

Thanks,
Jay


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