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Homogeneity of variance

Homogeneity of variance means equal variances between independent groups

The assumption of homogeneity of variance is important when conducting between-subjects statistics. The assumption is that the variances (and thus distributions) of independent groups on a continuous variable are similar, "equal," or "equivalent." Levene's Test of Equality of Variances is used to assess this statistical assumption.

If the p-value yielded from a Levene's test is less than .05, then the assumption of homogeneity of variance has been violated. Oftentimes, this is due to outliers in one or several of the independent groups that are being compared. Listwise deletion, logarithmic transformations, or non-parametric statistics can be used when the assumption of homogeneity of variance is violated.  

From a conceptual standpoint, the assumption of homogeneity of variance is an extension of the assumption of normality. It would not be feasible to compare a skewed distribution in one group to a normal distribution in another group. The two distributions are simply not comparable.

This assumption is important when using independent samples t-tests and one-way ANOVA. Click on the buttons below to see how the assumptions are assessed in SPSS.      

Homogeneity of variance and applied statistics

Independent Samples t-test
One-Way ANOVA
Back to Statistical Assumptions
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