Hi > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > project.org] On Behalf Of Andrej > Sent: Monday, October 14, 2013 9:49 AM > To: r-help@r-project.org > Subject: [R] Comparing two groups > > Hi, > this might sound trivial, but I'm pretty new to R and statistics in > general.
So why not start with some statistical textbook? There are plenty of them available in CRAN. > What I want to do is to compare two data values. The hook is, that they > are non-normally distributed and that one value is five times as big as > the other. The box-plots look like this > <http://r.789695.n4.nabble.com/file/n4678190/mixture_vs_monoculture.png > > . > Ignore the number at the bottom. I want to know if those two are > significantly different from one another. I tried it with the wilcox- > test (because it is advertised as a non-parametric test), but get a p- > value of > 0.0009 and naturally don't quite believe it to be true. Why? What leads you to this statement? Some other tests? Some other results? > Do you have any suggestions how I can handle that problem? You can try some normalising procedure like Box-Cox. function (x, lambda, inv = F) { if (!inv) { if (missing(lambda)) log(x) else (x^lambda - 1)/lambda } else (lambda * x + 1)^(1/lambda) } or boxcox from MASS package. and then to use standard t.test, but you will probably gat quite similar result as with wilcox.test. Regards Petr > > Andrej > > > > -- > View this message in context: http://r.789695.n4.nabble.com/Comparing- > two-groups-tp4678190.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. ______________________________________________ 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.
