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 -- 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.
