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Re: RE: st: Re: normal distributions


From   David Greenberg <dg4@nyu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: RE: st: Re: normal distributions
Date   Sun, 21 Jul 2002 17:23:23 -0400

Inferential statistics in OLS regression depend on the assumption that 
the distribution of residuals - that is to say, the distribution of 
scores on the dependent variable, conditional on the values of the 
predictors - is normal. The Central Limit Theorem is not relevant. It 
guarantees that parameter estimates will be normally distributed under 
certain circumstances. Those circumstances include the residuals being 
normally distributed. That is why, if the residuals are skewed, people 
transform variables or use estimation techniques other than OLS. David 
Greenberg, Sociology Department, New York University.

----- Original Message -----
From: "Michael Cha" <mikecha0@lycos.com>
Date: Sunday, July 21, 2002 4:37 pm
Subject: RE: st: Re: normal distributions

> Dear listers,
> 
> Could anyone tell me the relationship between regression 
> assumption test (Normality test in particular) and CLT (Central 
> Limit Theorem)? 
> 
> Does CLT imply that we do not have to worry about normality test 
> for residuals as far as sample size is large? 
> 
> Or CLT does not imply anything about the regression assumption 
> test? 
> 
> Thanks in advance,
> 
> MCHA,
> 
> 
> 
> 
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