Berton Gunter wrote:
Thanks for your suggestions, I undesrtand that! Could you possibly give me some (not too complicated!)Exactly! My point is that normality tests are useless for this purpose for
reasons that are beyond what I can take up here.
links so that I can investigate this matter further?
Cheers,
Federico
Hints: Balanced designs are
robust to non-normality; independence (especially "clustering" of subjects
due to systematic effects), not normality is usually the biggest real
statistical problem; hypothesis tests will always reject when samples are
large -- so what!; "trust" refers to prediction validity which has to do
with study design and the validity/representativeness of the current data to
future.
I know that all the stats 101 tests say to test for normality, but they're full of baloney!
Of course, this is "free" advice -- so caveat emptor!
Cheers, Bert
______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
