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Module « scipy.stats.mstats »

Fonction sem - module scipy.stats.mstats

Signature de la fonction sem

def sem(a, axis=0, ddof=1) 

Description

help(scipy.stats.mstats.sem)

Calculates the standard error of the mean of the input array.

Also sometimes called standard error of measurement.

Parameters
----------
a : array_like
    An array containing the values for which the standard error is
    returned.
axis : int or None, optional
    If axis is None, ravel `a` first. If axis is an integer, this will be
    the axis over which to operate. Defaults to 0.
ddof : int, optional
    Delta degrees-of-freedom. How many degrees of freedom to adjust
    for bias in limited samples relative to the population estimate
    of variance. Defaults to 1.

Returns
-------
s : ndarray or float
    The standard error of the mean in the sample(s), along the input axis.

Notes
-----
The default value for `ddof` changed in scipy 0.15.0 to be consistent with
`scipy.stats.sem` as well as with the most common definition used (like in
the R documentation).

Examples
--------
Find standard error along the first axis:

>>> import numpy as np
>>> from scipy import stats
>>> a = np.arange(20).reshape(5,4)
>>> print(stats.mstats.sem(a))
[2.8284271247461903 2.8284271247461903 2.8284271247461903
 2.8284271247461903]

Find standard error across the whole array, using n degrees of freedom:

>>> print(stats.mstats.sem(a, axis=None, ddof=0))
1.2893796958227628

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