🚀 go-pugleaf

In article <thompson.715720959@hermes.socsci.umn.edu>, thompson@atlas.socsci.umn.edu (T. Scott Thompson) writes:
> bateman@nsslsun.nssl.uoknor.edu (Monte Bateman) writes:
> 
>>I would like to test data for normality.  The books I have
>>access to talk about graphing frequencies on "probability paper".
> 
> Look up the Kolmogorov-Smirnov (sp?) statistic in a more advanced
> statistics text than the ones you have now.  

A clarification:  Using the K-S statistic to test for normality, 
calculated after plugging in the sample mean and variance in place of the 
population parameters, is known as
Lilliefors' [Strunk and White be damned!] test.

A Shapiro-Wilk test or a D'Agostino test would probably serve you better.
Lilliefors' test tends to be more sensitive to departures from normality
in the center of the distribution.  (One look at the test statistic will
reveal why.)  THe other tests tend to be more sensitive to departures
from normality in the tails, which is where non-normality is most often a
problem.  

This various tests have been compared most recently in, of all places, 
the Stata Technical Bulletin.  I dislike mentioning articles in a computer 
program's documentation/house organ because they are typically neither peer 
reviewed nor widely circulated, but it's there, so what can I say?
(I have heard rumors that Royston is preparing his contributions for formal 
publication, but they are only second hand rumors.)