[SciPy-Dev] two new scipy.stats requests code included:

[Paul Hobson]

Hey Jon,

To incorporate this into scipy, you'll need to open a pull request on
GitHub:
https://github.com/scipy/scipy

I'm not a scipy contributor, but I can tell you that you'll also need to
include tests that preferably use a (small) published dataset and confirm
that your function reproduce the published results.

Also, I don't think your return statements are behaving the way you think
they are. I believe that the preference is now to return a NamedTuple.

Hope that helps,
-Paul



On Mon, Oct 15, 2018 at 2:54 AM Jon Stein <oneday2one at icloud.com> wrote:

> Scipy-dev,
>
> Two additions to the scipy.stats module are missing and needed:
>
> One addition is needed for a one sample z-test including confidence
> interval when the population mean and standard deviation are known:
>
> def ztest(array_A, population_mean, population_stdv, level_of_confidence~*example:
> .95*):
>     z_statistic = (array_A.mean() - population_stdv) / (population_stdv /
> math.sqrt(len(array_A)))
>     p_value = (st.norm.cdf(z_stat))
>     standard_error = population_stdv / math.sqrt(len(array_A))
>     margin_of_error = st.norm.ppf(level_of_confidence) * standard_error
>     MoE = margin_of_error
>     return('z statistic =', z_statistic, 'p-value =', p_value,
> array_A.mean() - MoE, array_A.mean() + MoE)
>
> And one addition is needed for a one-sample z-test for a categorical
> sample (*not quantitative*):
>
> def ztest_1sample_categorical(sample_proportion, population_proportion,
> sample_size):
>     sp, pp = sample_proportion, population_proportion
>     z = (sp - pp) / math.sqrt((pp * (1 - pp)) / sample_size)
>     p = st.norm.cdf(z)
>     return('z statistic =', z, 'p value =', p)
>
> Let me know what you think.
> Jon Stein
>
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