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# scipy.stats.fligner

`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’. 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

  [R174] | http://www.stat.psu.edu/~bgl/center/tr/TR993.ps

  [R175] | 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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