statsmodels.stats.weightstats.CompareMeans.ztest_ind
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CompareMeans.ztest_ind(alternative='two-sided', usevar='pooled', value=0)
[source] -
z-test for the null hypothesis of identical means
Parameters: x1, x2 : array_like, 1-D or 2-D
two independent samples, see notes for 2-D case
alternative : string
The alternative hypothesis, H1, has to be one of the following ?two-sided?: H1: difference in means not equal to value (default) ?larger? : H1: difference in means larger than value ?smaller? : H1: difference in means smaller than value
usevar : string, ?pooled? or ?unequal?
If
pooled
, then the standard deviation of the samples is assumed to be the same. Ifunequal
, then Welsh ttest with Satterthwait degrees of freedom is usedvalue : float
difference between the means under the Null hypothesis.
Returns: tstat : float
test statisic
pvalue : float
pvalue of the t-test
df : int or float
degrees of freedom used in the t-test
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