[R] Outlier statistics question

Joshua Wiley jwiley.psych at gmail.com
Tue Nov 30 22:00:41 CET 2010

Hi Jahan,

What data are you going to use for analyses?  The original data or the
log transformed?  It does not make sense to evaluate your transformed
data for analysis based on the original untransformed data (unless you
are planning on using the untransformed for the analyses).

There is a several good fortunes on outliers:

fortune("just be an outlier")



On Tue, Nov 30, 2010 at 12:15 PM, Jahan <jahan.mohiuddin at 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).  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?
> ______________________________________________
> R-help at 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.

Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles

More information about the R-help mailing list