SciPy

scipy.stats.fligner

scipy.stats.fligner(*args, **kwds)[source]

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’.

proportiontocut : float, optional

When center is ‘trimmed’, this gives the proportion of data points to cut from each end. (See scipy.stats.trim_mean.) Default is 0.05.

Returns :

Xsq : float

the test statistic

p-value : float

the p-value for the hypothesis test

Notes

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.

References

[R228]http://www.stat.psu.edu/~bgl/center/tr/TR993.ps
[R229]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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