What is the purpose of homogeneity of variance test?

Levene’s test ( Levene 1960) is used to test if k samples have equal variances. Equal variances across samples is called homogeneity of variance. Some statistical tests, for example the analysis of variance, assume that variances are equal across groups or samples. The Levene test can be used to verify that assumption.

What is the assumption of the equality of variances?

The assumption of equal variances (i.e. assumption of homoscedasticity) assumes that different samples have the same variance, even if they came from different populations. The assumption is found in many statistical tests, including Analysis of Variance (ANOVA) and Student’s T-Test.

What is homogeneity of variance covariance?

the condition in which multiple groups in an experimental design have the same covariance matrix. A basic assumption in a multivariate analysis of variance, it is the multivariate analog of homogeneity of variance.

Why does homogeneity of variance matter?

In short, homogeneity of variance is key because otherwise you just don’t know if the independent variables you have selected within your multiple regression model are statistically significant.

What are the assumptions of analysis of variance?

Assumptions of ANOVA . The following assumptions exist when you perform an analysis of variance: The expected values of the errors are zero. The variances of all errors are equal to each other. The errors are independent from one another. The errors are normally distributed.

What does it mean to assume equal variance?

The assumption of equal variances (i.e. assumption of homoscedasticity ) assumes that different samples have the same variance, even if they came from different populations. The assumption is found in many statistical tests, including Analysis of Variance (ANOVA) and Student’s T-Test.

What does it mean for variances to be equal?

Statistical tests, such as analysis of variance ( ANOVA ), assume that although different samples can come from populations with different means, they have the same variance. Equal variances (homoscedasticity) is when the variances are approximately the same across the samples.