# Homogeneity of variance

## Homogeneity of variance means equal variances between independent groups

The assumption of

If the

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

**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

**yielded from a Levene's test is***p*-value**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

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