has_specified_input
has_specified_output
achieves_planned_objective
p-value
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 Brownâ€“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
ready for release