Bartlett’s test (introduced in 1937 by Maurice Barlett (1910–2002)) is an inferential procedure used to assess the equality of variance in different populations (not in samples as sometimes can be found, since there is no point in testing whether the samples have equal variances – we can always easily calculate and compare their values). Some common statistical methods assume that variances of the populations from which different samples are drawn are equal. Bartlett’s test assesses this assumption. It tests the null hypothesis that the population variances are equal.
All statistical procedures have underlying assumptions. In some cases, violation of these assumptions will not change substantive research conclusions. In other cases, violation of assumptions is critical to meaningful research. Establishing that one’s data meet the assumptions of the procedure one is using is an expected component of all quantitatively based journal articles, theses, and dissertations. The following are...
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Arsham, H., Lovric, M. (2011). Bartlett’s Test. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_132
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