2010/6/25 Frank E Harrell Jr <f.harr...@vanderbilt.edu>: > The central limit theorem doesn't help. It just addresses type I error, > not power. > > Frank
I don't think I stated otherwise. I am aware of the fact that the wilcoxon has an Asymptotic Relative Efficiency greater than 1 compared to the t-test in case of skewed distributions. Apologies if I caused more confusion. The "problem" with the wilcoxon is twofold as far as I understood this data correctly : - there are quite some ties - the wilcoxon assumes under the null that the distributions are the same, not only the location. The influence of unequal variances and/or shapes of the distribution is enhanced in the case of unequal sample sizes. The central limit theory makes that : - the t-test will do correct inference in the presence of ties - unequal variances can be taken into account using the modified t-test, both in the case of equal and unequal sample sizes For these reasons, I would personally use the t-test for comparing two samples from the described population. Your mileage may vary. Cheers Joris > > On 06/25/2010 04:29 AM, Joris Meys wrote: >> As a remark on your histogram : use less breaks! This histogram tells >> you nothing. An interesting function is ?density , eg : >> >> x<-rnorm(250) >> hist(x,freq=F) >> lines(density(x),col="red") >> >> See also this ppt, a very nice and short introduction to graphics in R : >> http://csg.sph.umich.edu/docs/R/graphics-1.pdf >> >> 2010/6/25 Atte Tenkanen<atte...@utu.fi>: >>> Is there anything for me? >>> >>> There is a lot of data, n=2418, but there are also a lot of ties. >>> My sample n≈250-300 >> >> You should think about the central limit theorem. Actually, you can >> just use a t-test to compare means, as with those sample sizes the >> mean is almost certainly normally distributed. >>> >>> i would like to test, whether the mean of the sample differ significantly >>> from the population mean. >>> >> According to probability theory, this will be in 5% of the cases if >> you repeat your sampling infinitly. But as David asked: why on earth >> do you want to test that? >> >> cheers >> Joris >> > > > -- > Frank E Harrell Jr Professor and Chairman School of Medicine > Department of Biostatistics Vanderbilt University > -- Joris Meys Statistical consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php ______________________________________________ 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.