[EMAIL PROTECTED] (Paul R Swank) wrote in 
007d01c290b4$adee3de0$520e6a81@PEDUCT225:">news:007d01c290b4$adee3de0$520e6a81@PEDUCT225:
>the websites posted below gave me some problems
Cannot explain why it couldn't be found. It's always been there when I 
looked. The second link required either that I get a newsreader that 
doesn't wrap (sorry, I like my newsreader) or that you cut and paste the 
broken URL. It's still there when I cut and paste from your reply and 
delivering graphical depictions of non-central t's.
> If the
> assumptions for t are met, that is, the observations are NID with equal
> variances, why would the non-central t be asymmetric.
> 
Think of the joint probability of the normal pdf on the x-axis and the chi-
square pdf with more than one df on the y-axis. In the central-T you are 
"looking" at the joint distribution from "below" the middle of the normal 
distribution (x=0), whereas in the non-central T you are "looking" 
(double integration, really) at the joint distribution from the origin. The 
joint density is shifted over to the right or left depending on the non-
centrality parameter. The asymmetry comes from the side-long look at the 
chi-square (or chi) distribution along lines radiating out from the origin 
with various slopes.

Let me admit that if I were using my "intuition" that I would have 
predicted that the skewness would be opposite to what happens, but that 
probably comes from my not being able to adjust for the ratio of x/y in the 
integration.

David Winsemius.
.
.
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