Should I assume equal or unequal variance?

Should I assume equal or unequal variance?

Use the Variance Rule of Thumb. 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 Student’s t-test.

How do you know if variances are equal or unequal?

F Test to Compare Two Variances If the variances are equal, the ratio of the variances will equal 1. For example, if you had two data sets with a sample 1 (variance of 10) and a sample 2 (variance of 10), the ratio would be 10/10 = 1. You always test that the population variances are equal when running an F Test.

Why do we assume equal variances in t test?

A two sample t test assuming equal variances is used to test data to see if there is statistical significance or if the results may have occurred randomly. This is one of three t tests available in Excel and of the three, it’s the one least likely to be used. Why?

What does it mean to assume equal variance?

What Is the Assumption of Equal Variance? 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.

How do you tell if the difference between two means is significant?

When the P-value is less than 0.05 (P<0.05), the conclusion is that the two means are significantly different. Note that in MedCalc P-values are always two-sided (or two-tailed).

What are the three assumptions that have to be made to use Anova?

The factorial ANOVA has a several assumptions that need to be fulfilled – (1) interval data of the dependent variable, (2) normality, (3) homoscedasticity, and (4) no multicollinearity.

When can you assume homogeneity of variance?

If the two variances are equal, then the ratio of the variances equals 1.00. Therefore, the null hypothesis is . When this null hypothesis is not rejected, then homogeneity of variance is confirmed, and the assumption is not violated.

When can we assume equal population variances?

Two sample standard deviations are very similar so we will assume equal population variances. 95% confidence interval contains 0 so cannot rule out that the population means may be equal. If sample sizes are equal, the pooled and unpooled standard errors are equal.