Any reasonable test of whether two samples differ should be scale and location invariant. E.g., if you measure temperature it should not matter if you units are degrees Fahrenheit or micro-Kelvins. Thus saying the medians are 3500 and 6200 is equivalent to saying they are 100.035 and 100.062: it does not tell use how different the samples are. You need to consider how much overlap there is.
Bill Dunlap TIBCO Software wdunlap tibco.com On Tue, Mar 19, 2019 at 9:48 AM javed khan <javedbtk...@gmail.com> wrote: > Hi > > This is my function: > > wilcox.test(A,B, data = data, paired = FALSE) > > It gives me high p value, though the median of A column is 6900 and B > column is 3500. > > Why it gives p value high if there is a difference in the median? > > Regards > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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 -- To UNSUBSCRIBE and more, see 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.
