Re: st: Normally distributed error term & testing normality of residuals

["Justina Fischer" <JAVFischer@gmx.de>]

A formal test of normality would be the Jarque-Bera-test of normality, available as user written programme called -jb6-. 
It gives nice test stats that can be reported in a paper.
(is there s.th. newer available?)

I prefer using the Jarque-Bera combined with -qnorm- (see below, which allows to label the single obs) in order to identify outlier observations. 

Justina




-------- Original-Nachricht --------
> Datum: Sat, 13 Oct 2012 12:42:58 +0100
> Von: Nick Cox <njcoxstata@gmail.com>
> An: statalist@hsphsun2.harvard.edu
> Betreff: Re: st: Normally distributed error term & testing normality of residuals

> You don't say what kind of model you are fitting.
> 
> -qnorm- allows a more incisive graphical assessment of normality than
> -histogram, normal-. It doesn't offer a formal significance test.
> People who are well informed on the matter don't agree: some would
> always seek a formal test, others are happy to think about the results
> of -qnorm- in context.
> 
> Even when normality of error terms is an explicit assumption behind a
> model, it is typically also the least important assumption.
> 
> Nick
> 
> On Sat, Oct 13, 2012 at 12:06 PM, Ebru Ozturk <ebru_0512@hotmail.com>
> wrote:
> 
> > I test for normality of residuals with the command below:
> >
> > predict e, resid
> > histogram e, normal
> >
> > So, does this command also work for understanding of whether error term
> normally distributed or not?
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