# statsmodels.stats.weightstats.CompareMeans¶

class statsmodels.stats.weightstats.CompareMeans(d1, d2)[source]

class for two sample comparison

The tests and the confidence interval work for multi-endpoint comparison: If d1 and d2 have the same number of rows, then each column of the data in d1 is compared with the corresponding column in d2.

Parameters
d1, d2instances of DescrStatsW

Notes

The result for the statistical tests and the confidence interval are independent of the user specified ddof.

TODO: Extend to any number of groups or write a version that works in that case, like in SAS and SPSS.

Methods

 degrees of freedom of Satterthwaite for unequal variance from_data(data1, data2[, weights1, …]) construct a CompareMeans object from data variance assuming equal variance in both data sets summary([use_t, alpha, usevar, value]) summarize the results of the hypothesis test tconfint_diff([alpha, alternative, usevar]) confidence interval for the difference in means ttest_ind([alternative, usevar, value]) ttest for the null hypothesis of identical means ttost_ind(low, upp[, usevar]) test of equivalence for two independent samples, base on t-test zconfint_diff([alpha, alternative, usevar]) confidence interval for the difference in means ztest_ind([alternative, usevar, value]) z-test for the null hypothesis of identical means ztost_ind(low, upp[, usevar]) test of equivalence for two independent samples, based on z-test
 std_meandiff_separatevar