What does it mean if equal variances are assumed?

What does it mean if equal variances are assumed?

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.

Should equal variances be assumed?

Equal variances assumed Because we assume equal population variances, it is OK to “pool” the sample variances (sp). However, if this assumption is violated, the pooled variance estimate may not be accurate, which would affect the accuracy of our test statistic (and hence, the p-value).

What does test for equal variances tell you?

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.

Why is it important to have equal variance?

It is important because it is a formal requirement for statistical analyses such as ANOVA or the Student’s t-test. The unequal variance doesn’t have much impact on ANOVA if the data sets have equal sample sizes. However, if the sample sizes are different, ANOVA will end up with inaccurate results.

How do you assess equal variance assumption?

Use the rule of thumb ratio. As a rule of thumb, if the ratio of the larger variance to the smaller variance is less than 4, then we can assume the variances are approximately equal and use the two sample t-test. For example, suppose sample 1 has a variance of 24.5 and sample 2 has a variance of 15.2.

How do you assume equal variances with two samples?

Use the Variance Rule of Thumb. For example, suppose we have the following two samples: What is this? Sample 1 has a variance of 24.86 and sample 2 has a variance of 15.76. Since this ratio is less than 4, we could assume that the variances between the two groups are approximately equal.

What are the assumptions of a two-sample t test with variances not assumed equal?

Test Assumptions When running a two-sample equal-variance t-test, the basic assumptions are that the distributions of the two populations are normal, and that the variances of the two distributions are the same.

What is the difference between equal variance and UNequal variance?

The Two-Sample assuming Equal Variances test is used when you know (either through the question or you have analyzed the variance in the data) that the variances are the same. The Two-Sample assuming UNequal Variances test is used when either: You know the variances are not the same.