scipy.stats.mstats.ttest_onesamp#
- scipy.stats.mstats.ttest_onesamp(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)
New in version 1.7.0.
- Returns:
- statisticfloat or array
t-statistic
- pvaluefloat or array
The p-value
Notes
For more details on
ttest_1samp
, seescipy.stats.ttest_1samp
.