'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. If ``unequal``, then the standard deviations of the samples may
be different.
value : float
difference between the means under the Null hypothesis.
Returns
tstat : float
test statisic
pvalue : float
pvalue of the z-test'

def ztest_ind(self, alternative='two-sided', usevar='pooled', value=0):

    d1 = self.d1
    d2 = self.d2
    if (usevar == 'pooled'):
        stdm = self.std_meandiff_pooledvar
    elif (usevar == 'unequal'):
        stdm = self.std_meandiff_separatevar
    else:
        raise ValueError('usevar    can    only    be    "pooled"    or    "unequal"')
    (tstat, pval) = _zstat_generic(d1.mean, d2.mean, stdm, alternative, diff=value)
    return (tstat, pval)
