scipy.stats.mstats.ttest_1samp#

scipy.stats.mstats.ttest_1samp(a, popmean, axis=0, alternative='two-sided')[source]#

Calculates the T-test for the mean of ONE group of scores.

Parameters:

aarray_like

sample observation

popmeanfloat or array_like

expected value in null hypothesis, if array_like than it must have the same shape as a excluding the axis dimension

axisint or None, optional

Axis along which to compute test. If None, compute over the whole array a.

alternative{‘two-sided’, ‘less’, ‘greater’}, optional

Defines the alternative hypothesis. The following options are available (default is ‘two-sided’):

‘two-sided’: the mean of the underlying distribution of the sample is different than the given population mean (popmean)
‘less’: the mean of the underlying distribution of the sample is less than the given population mean (popmean)
‘greater’: the mean of the underlying distribution of the sample is greater than the given population mean (popmean)

Added in version 1.7.0.

Returns:

Notes