Thanks, would it be possible to give an example of how I can have more specific null hypothesis in R? I am not aware of how to specify it for the K-S test in R.
And repeating my second question, what is a good way to measure the difference between observed and expected samples? Is the D statistic of the KS test a good choice? Nitin On Thu, Aug 21, 2008 at 7:40 PM, Moshe Olshansky <[EMAIL PROTECTED]>wrote: > Hi Nitin, > > I believe that you can not have null hypothesis to be that A and B come > from different distributions. > Asymptotically (as both sample sizes go to infinity) KS test has power 1, > i.e. it will reject H0:A=B for any case where A and B have different > distributions. > To work with a finite sample you must be more specific, i.e. your null > hypothesis must be not that A and B just have different distributions but > must be more specific, i.e that their means are different by at least > something or that certain distance between their distributions is bigger > than something, etc. and such hypotheses can be tested (and rejected). > > > --- On Fri, 22/8/08, Nitin Agrawal <[EMAIL PROTECTED]<[EMAIL PROTECTED]>> > wrote: > > > From: Nitin Agrawal <[EMAIL PROTECTED]<[EMAIL PROTECTED]> > > > > Subject: [R] Null and Alternate hypothesis for Significance test > > To: r-help@r-project.org > > Received: Friday, 22 August, 2008, 6:58 AM > > Hi, > > I had a question about specifying the Null hypothesis in a > > significance > > test. > > Advance apologies if this has already been asked previously > > or is a naive > > question. > > > > I have two samples A and B, and I want to test whether A > > and B come from > > the same distribution. The default Null hypothesis would be > > H0: A=B > > But since I am trying to prove that A and B indeed come > > from the same > > distribution, I think this is not the right choice for the > > null hypothesis > > (it should be one that is set up to be rejected) > > > > How do I specify a null hypothesis H0: A not equal to B for > > say a KS test. > > An example to do this in R would be greatly appreciated. > > > > On a related note: what is a good way to measure the > > difference between > > observed and expected PDFs? Is the D statistic of the KS > > test a good choice? > > > > Thanks! > > Nitin > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, > > reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
