Re: Are the scores normally distributed?

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On Fri, Dec 7, 2018 at 12:08 PM Paul Hobson <[email protected]> wrote:

> I think you misunderstand the null hypothesis.
>
> The null hypothesis for this test is that the data are *not* normally
> distributed.
>

That's not correct. The null hypothesis is the data come from a normal
distribution.

My guess is that because of the relatively large sample size, the power is
quite large and the test detects relatively small deviation from normality.

len(x)
Out[8]: 1444

stats.skewtest(x)
Out[9]: SkewtestResult(statistic=1.79241121722139,
pvalue=0.073067119279312559)

stats.kurtosistest(x)
Out[10]: KurtosistestResult(statistic=3.5348152259352097,
pvalue=0.00040806039300234271)

According the the two separate tests that are combined in the normal test,
the data has heavier tails, larger kurtosis than the normal distribution.

(Using kstest as distance measure, however, shows that the normal
distribution matches the data better than a t distribution with smaller df.
Note, pvalues for kstest don't apply because loc and scale are estimated.)

Josef




>
> Since the p-value is your examples is 0.0003 (i.e., less than 0.001), you
> can reject the null hypothesis, suggesting that your data are normally
> distributed.
> -Paul
>
> On Fri, Dec 7, 2018 at 8:54 AM Bakary N'tji Diallo <
> [email protected]> wrote:
>
>> Dear all,
>> Hope you are doing very well.
>>
>> I am trying to apply a statistical normalization which require the values
>> to be normally distributed.
>> I have prepared a short notebook with all details.
>>
>> https://nbviewer.jupyter.org/github/diallobakary4/bioinformatics/blob/master/Normatily_test.ipynb
>>
>> It will be great if someone can help me out.
>>
>> Thanks
>> Best regards
>> --
>>
>> Bakary N’tji DIALLO
>>
>> PhD Student (Bioinformatics) <http://linkedin.com/in/bakarydiallo>, Research
>> Unit in Bioinformatics (RUBi) <https://rubi.ru.ac.za/>
>>
>> Mail: [email protected] |  Skype: diallobakary4
>>
>> Tel: +27798233845 | +223 74 56 57 22 | +223 97 39 77 14
>>
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