(Apologies to all. I am weak and could not resist) On Tue, Nov 30, 2010 at 12:15 PM, Jahan <jahan.mohiud...@gmail.com> wrote: > I have a statistical question. > The data sets I am working with are right-skewed so I have been > plotting the log transformations of my data. I am using a Grubbs Test > to detect outliers in the data, but I get different outcomes depending > on whether I run the test on the original data or the log(data).
Of course! Here > is one of the problematic sets: > > fgf2p50=c(1.563,2.161,2.529,2.726,2.442,5.047) > stripchart(fgf2p50,vertical=TRUE) > #This next step requires you have the 'outliers' package > library(outliers) > grubbs.test(fgf2p50) > #the output says p<0.05 so 5.047 is an outlier > #Next, I run the test on the log(data) > log10=c(0.194,0.335,0.403,0.436,0.388,0.703) > grubbs.test(log10) > #output is that p>0.05 so we reject that there is an outlier. > > The question is, which outlier test do I accept? Neither. (IMHO) Outlier tests are one of statistics's _bad ideas._ The Grubbs test is ca 1970 . There are many better approaches these days -- consult your local statistician -- all of which will depend on answering the question, "What is the question you are trying to answer?" -- Bert > > ______________________________________________ > 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. > -- Bert Gunter Genentech Nonclinical Biostatistics ______________________________________________ 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.