scipy.stats.fligner(*args, **kwds)

Perform Fligner’s test for equal variances

Fligner’s test tests the null hypothesis that all input samples are from populations with equal variances. Fligner’s test is non-parametric in contrast to Bartlett’s test bartlett_ and Levene’s test levene_.

Parameters :

sample1, sample2, ... : array_like

arrays of sample data. Need not be the same length

center : {‘mean’, ‘median’, ‘trimmed’}, optional

keyword argument controlling which function of the data is used in computing the test statistic. The default is ‘median’.

Returns :

Xsq : float

the test statistic

p-value : float

the p-value for the hypothesis test


As with Levene’s test there are three variants of Fligner’s test that differ by the measure of central tendency used in the test. See levene_ for more information.


[R51]Fligner, M.A. and Killeen, T.J. (1976). Distribution-free two-sample tests for scale. ‘Journal of the American Statistical Association.’ 71(353), 210-213.

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