In article <[EMAIL PROTECTED]>, Rajarshi Guha <[EMAIL PROTECTED]> wrote: >Hi, > I'm working on a problem in which I'd like to determine whether two >sets of data come from the same distribution. It seems that the Kolmogorv >Smirnov test will give me the information I need.
>However I'd like to go further than just accept or reject the H0 for the >test. Is there any way (using this test or someother test) to determine >*how* similar the distributions of two sets are? >Am I correct in thinking that a P value for the KS test would provide this >information? I looked up Conovers book on non parametric statistics for >the algorithm of the KS test. However it does not mention any way of >calculating a P for the test. Is it possible? >Are there any other tests that would be able to tell me how similar the >distributions of two sets of observations are How close two distributions are is NOT a problem of statistics. It is the user who should decide the measure of closeness. Statistics can then be used to test whether the observed distance can be due to chance. The test used should depend on the measure chosen by the user. The closeness of distributions is not affected by sample size; the ease of detecting it is, both by the sample size and the test chosen. -- This address is for information only. I do not claim that these views are those of the Statistics Department or of Purdue University. Herman Rubin, Department of Statistics, Purdue University [EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558 . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
