Vous êtes un professionnel et vous avez besoin d'une formation ? Programmation Python
Les fondamentaux Voir le programme détaillé

Module « scipy.stats »

Fonction obrientransform - module scipy.stats

Signature de la fonction obrientransform

def obrientransform(*samples) 

Description

help(scipy.stats.obrientransform)

Compute the O'Brien transform on input data (any number of arrays).

Used to test for homogeneity of variance prior to running one-way stats.
Each array in ``*samples`` is one level of a factor.
If `f_oneway` is run on the transformed data and found significant,
the variances are unequal.  From Maxwell and Delaney [1]_, p.112.

Parameters
----------
sample1, sample2, ... : array_like
    Any number of arrays.

Returns
-------
obrientransform : ndarray
    Transformed data for use in an ANOVA.  The first dimension
    of the result corresponds to the sequence of transformed
    arrays.  If the arrays given are all 1-D of the same length,
    the return value is a 2-D array; otherwise it is a 1-D array
    of type object, with each element being an ndarray.

Raises
------
ValueError
    If the mean of the transformed data is not equal to the original
    variance, indicating a lack of convergence in the O'Brien transform.

References
----------
.. [1] S. E. Maxwell and H. D. Delaney, "Designing Experiments and
       Analyzing Data: A Model Comparison Perspective", Wadsworth, 1990.

Examples
--------
We'll test the following data sets for differences in their variance.

>>> x = [10, 11, 13, 9, 7, 12, 12, 9, 10]
>>> y = [13, 21, 5, 10, 8, 14, 10, 12, 7, 15]

Apply the O'Brien transform to the data.

>>> from scipy.stats import obrientransform
>>> tx, ty = obrientransform(x, y)

Use `scipy.stats.f_oneway` to apply a one-way ANOVA test to the
transformed data.

>>> from scipy.stats import f_oneway
>>> F, p = f_oneway(tx, ty)
>>> p
0.1314139477040335

If we require that ``p < 0.05`` for significance, we cannot conclude
that the variances are different.

Vous êtes un professionnel et vous avez besoin d'une formation ? Mise en oeuvre d'IHM
avec Qt et PySide6 Voir le programme détaillé