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In statistics, a sequence of random variables is homoscedastic (/ ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k /) if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance.
Statistical testing for a non-zero heterogeneity variance is often done based on Cochran's Q [13] or related test procedures. This common procedure however is questionable for several reasons, namely, the low power of such tests [14] especially in the very common case of only few estimates being combined in the analysis, [15] [7] as well as the specification of homogeneity as the null ...
Cultural consensus theory assumes that cultural beliefs are learned and shared across people and that there is a common understanding of what the world and society are all about. [2] Since the amount of information in a culture is too large for any one individual to master, individuals know different subsets of the cultural knowledge and vary ...
A diversity index is a method of measuring how many different types (e.g. species) there are in a dataset (e.g. a community).Diversity indices are statistical representations of different aspects of biodiversity (e.g. richness, evenness, and dominance), which are useful simplifications for comparing different communities or sites.
In statistics, Bartlett's test, named after Maurice Stevenson Bartlett, [1] is used to test homoscedasticity, that is, if multiple samples are from populations with equal variances. [2] Some statistical tests, such as the analysis of variance, assume that variances are equal across groups or samples, which can be checked with Bartlett's test.
Funnel plots, introduced by Light and Pillemer in 1984 [1] and discussed in detail by Matthias Egger and colleagues, [2] [3] are useful adjuncts to meta-analyses. A funnel plot is a scatterplot of treatment effect against a measure of study precision. It is used primarily as a visual aid for detecting bias or systematic heterogeneity.
In this case, the beta-binomial model distribution is a popular and analytically tractable alternative model to the binomial distribution since it provides a better fit to the observed data. [2] To capture the heterogeneity of the families, one can think of the probability parameter of the binomial model (say, probability of being a boy) is ...
[1] [2] [3] It is named after William Gemmell Cochran. Cochran's Q test should not be confused with Cochran's C test , which is a variance outlier test. Put in simple technical terms, Cochran's Q test requires that there only be a binary response (e.g. success/failure or 1/0) and that there be more than 2 groups of the same size.