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Re: Determining if samples are normal


From: Mike Miller
Subject: Re: Determining if samples are normal
Date: Mon, 26 Sep 2005 19:11:18 -0500 (CDT)

On Mon, 26 Sep 2005, Paul Kienzle wrote:

Using n=400, 60% of the triangular samples are rejected at a .1 level, but of course 10% of the normal samples are as well.


So maybe the q-q correlation method is more powerful than Anderson-Darling in this case. In the q-q correlation method, with n=300, we could reject 49% at the .05 level. Of course 49% is less than 60%, but that was achieved with a smaller sample size and half the type-1 error rate.

By the way, I did a little test to confirm that the published critical value was approximately correct:

for i=1:10000, r(i)=corrcoef([normals,sort(randn(300,1))])(2,1); end
mean(r < .9953)
ans = 0.050600

Mike



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