Skip to main content

Heterogeneity of Variance

Edited by: Published: 2017
+- LessMore information
Download PDF

Heterogeneity of variance refers to the violation of the homogeneity of variance assumption, one of the main assumptions underlying the analysis of grouped data in the univariate and multivariate contexts (i.e., independent samples t-test, analysis of variance [ANOVA], and multivariate analysis of variance [MANOVA]). Broadly speaking, heterogeneity of variance means that the population variances of the groups or cells being compared are not homogenous or equal. Because variances are averaged in the calculation of standard error and error terms, under the assumption they are roughly equal, heterogeneity will create bias and inconsistencies in significance tests and confidence intervals for the model under consideration. Heterogeneity of variance is a special instance of what is known as heteroscedasticity in the context of regression, the only ...

Looks like you do not have access to this content.

Reader's Guide

  • All
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z

      Copy and paste the following HTML into your website