sem#
- sem(a, axis=None, *args, **kwargs)[source]#
Calculate the standard error of the mean (SEM).
Shortcut (for a 1D array) to
array.std()/np.sqrt(len(array)).- Parameters:
a (arr) – array to calculate the SEM of
axis (int) – axis to calculate the SEM along
kwargs (dict) – passed to
numpy.std()
Example:
data = np.random.randn(100) sem = sc.sem(data) # Roughly 0.1
New in version 3.2.0.