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# scipy.stats.ttest_ind_from_stats

`scipy.stats.``ttest_ind_from_stats`(mean1, std1, nobs1, mean2, std2, nobs2, equal_var=True)

  T-test for means of two independent samples from descriptive statistics.

  This is a two-sided test for the null hypothesis that 2 independent samples have identical average (expected) values.

  Parameters: | mean1 : array_like The mean(s) of sample 1. std1 : array_like The standard deviation(s) of sample 1. nobs1 : array_like The number(s) of observations of sample 1. mean2 : array_like The mean(s) of sample 2 std2 : array_like The standard deviations(s) of sample 2. nobs2 : array_like The number(s) of observations of sample 2. equal_var : bool, optional If True (default), perform a standard independent 2 sample test that assumes equal population variances [R368]. If False, perform Welch’s t-test, which does not assume equal population variance [R369].
  Returns: | statistic : float or array The calculated t-statistics pvalue : float or array The two-tailed p-value.

  See also

  `scipy.stats.ttest_ind`

  Notes

  New in version 0.16.0.

  References

  [R368] | (1, 2) http://en.wikipedia.org/wiki/T-test#Independent_two-sample_t-test

  [R369] | (1, 2) http://en.wikipedia.org/wiki/Welch%27s_t_test