of Harold Hotelling, I. Olkin et al. eds.,
       Stanford University Press, pp. 278-292.
.. [3] Brown, M. B. and Forsythe, A. B. (1974), Journal of the American
       Statistical Association, 69, 364-367

Examples
--------

Test whether the lists `a`, `b` and `c` come from populations
with equal variances.

>>> import numpy as np
>>> from scipy import stats
>>> a = [8.88, 9.12, 9.04, 8.98, 9.00, 9.08, 9.01, 8.85, 9.06, 8.99]
>>> b = [8.88, 8.95, 9.29, 9.44, 9.15, 9.58, 8.36, 9.18, 8.67, 9.05]
>>> c = [8.95, 9.12, 8.95, 8.85, 9.03, 8.84, 9.07, 8.98, 8.86, 8.98]
>>> stat, p = stats.levene(a, b, c)
>>> p
0.002431505967249681

The small p-value suggests that the populations do not have equal
variances.

This is not surprising, given that the sample variance of `b` is much
larger than that of `a` and `c`:

>>> [np.var(x, ddof=1) for x in [a, b, c]]
[0.007054444444444413, 0.13073888888888888, 0.008890000000000002]

For a more detailed example, see :ref:`hypothesis_levene`.
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