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


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Normally distributed error term & testing normality of residuals
Date   Sun, 14 Oct 2012 01:15:43 +0100

As said, I agree that -qnorm- is a good idea. See

http://www.stata.com/statalist/archive/2012-09/msg01013.html

http://www.stata.com/statalist/archive/2012-09/msg01040.html

for why not to choose Jarque-Bera.

Nick

On Sun, Oct 14, 2012 at 12:09 AM, Justina Fischer <JAVFischer@gmx.de> wrote:
> 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.

Nick Cox <njcoxstata@gmail.com>

>> 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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