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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

  [R80] | http://www.stat.psu.edu/~bgl/center/tr/TR993.ps

  [R81] | 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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