has_specified_input has_specified_output achieves_planned_objective data transformation false positive rate Barlett's test Orlaith Burke Alejandra Gonzalez-Beltran Bartlett's test (see Snedecor and Cochran, 1989) is used to test if k samples are from populations with equal variances. Equal variances across samples is called homoscedasticity or homogeneity of variances. Some statistical tests, for example the analysis of variance, assume that variances are equal across groups or samples. The Bartlett test can be used to verify that assumption. Bartlett's test is sensitive to departures from normality. That is, if the samples come from non-normal distributions, then Bartlett's test may simply be testing for non-normality. Levene's test and the Brown–Forsythe test are alternatives to the Bartlett test that are less sensitive to departures from normality. Philippe Rocca-Serra bartlett.test(x) function, where x is a numeric vector http://en.wikipedia.org/wiki/Bartlett_test scipy.stats.bartlett(*args) http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.bartlett.html#scipy.stats.bartlett source: https://github.com/scipy/scipy/blob/v0.15.1/scipy/stats/morestats.py#L1450 homoskedasticity test goodness of fit statistical test goodness of fit testing objective equal variance testing objective continuous variable categorical variable p-value ready for release