search for: fgf2p50

...ets 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...