For the two sample situation, the t test and ANOVAs F test are equivalent in terms of the results. For non-parametric, the typical choices are the Wilcoxon and the Kruskal-Wallis test.
Paul R. Swank, Ph.D. Professor, Developmental Pediatrics Medical School UT Health Science Center at Houston -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of seferiad Sent: Thursday, September 25, 2003 8:57 AM To: [EMAIL PROTECTED] Subject: nonparametic "F test" 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 . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . ================================================================= . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
