Bartlett's test

Bartlett's test

Bartlett's test (Snedecor and Cochran, 1983) is used to test if k samples have 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 your samples come from non-normal distributions, then Bartlett's test may simply be testing for non-normality. The Levene test and Brown-Forsythe test are alternatives to the Bartlett test that are less sensitive to departures from normality.

Bartlett's test is used to test the null hypothesis, H_0 that all k population variances are equal against the alternative that at least two are different.

If there are k samples with size n_i and sample variance S_i^2 then Bartlett's test statistic is :X^2 = frac{(N-k)ln(S_p^2) - sum_{i=1}^k(n_i - 1)ln(S_i^2)}{1 + frac{1}{3(k-1)}left(sum_{i=1}^k(frac{1}{n_i-1}) - frac{1}{N-k} ight)}where N = sum_{i=1}^k n_i and S_p^2 = frac{1}{N-k} sum_i (n_i-1)S_i^2 is the pooled estimate for the variance.

The test statistic has approximately a chi^2_{k-1} distribution. Thus the null hypothesis is rejected if X^2 > chi^2_{k-1,alpha} (where chi^2_{k-1,alpha} is the upper tail critical value for the chi^2_{k-1} distribution).

Bartlett's test is a modification of the corresponding likelihood ratio test designed to make the approximation to the chi^2_{k-1} distribution better (M. S. Bartlett 1937).

ee also

* M. S. Bartlett

References

*Bartlett, M. S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Statistical Society Series A 160, 268–282.
*Snedecor, George W. and Cochran, William G. (1989), Statistical Methods, Eighth Edition, Iowa State University Press.

External links

* [http://www.itl.nist.gov/div898/handbook/eda/section3/eda357.htm NIST page on Bartlett's test]


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