Does two-sample t-test assume equal variance?
The t-Test Paired Two-Sample for Means tool performs a paired two-sample Student’s t-Test to ascertain if the null hypothesis (means of two populations are equal) can be accepted or rejected. This test does not assume that the variances of both populations are equal.
Do you need variance for t-test?
A t-test looks at the t-statistic, the t-distribution values, and the degrees of freedom to determine the statistical significance. To conduct a test with three or more means, one must use an analysis of variance.
How do you know if a t-test is significant?
If it is less than α, reject the null hypothesis. If the result is greater than α, fail to reject the null hypothesis. If you reject the null hypothesis, this implies that your alternative hypothesis is correct, and that the data is significant.
What is meant by equal 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.
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.
What does it mean by equal variance?
Equal variances (homoscedasticity) is when the variances are approximately the same across the samples. If you are comparing two or more sample means, as in the 2-Sample t-test and ANOVA, a significantly different variance could overshadow the differences between means and lead to incorrect conclusions.
Can you do a t-test with unequal sample sizes?
Even though you can perform a t-test when the sample size is unequal between two groups, it is more efficient to have an equal sample size in two groups to increase the power of the t-test. Welch’s t-test is for unequal variance data.
How is the unequal variance t test computed?
The unequal variance t test reports a confidence interval for the difference between two means that is usable even if the standard deviations differ. How the unequal variance t test is computed. Both t tests report both a P value and confidence interval.
When do you use two sample t test?
Two-Sample T-Tests Allowing Unequal Variance Introduction This procedure provides sample size and power calculations for one- or two-sided two-sample t-tests when no assumption of equal variances for the two population is made. This is commonly known as the Aspin-Welch test, Welch’s t-test (Welch, 1937), or the Satterthwaite method.
Which is the best tool to test for unequal variances?
We can also use Excel’s t-Test: Two-Sample Assuming Unequal Variances data analysis tool to get the same result (see Figure 2). Observation: Generally, even if one variance is up to 3 or 4 times the other, the equal variance assumption will give good results, especially if the sample sizes are equal or almost equal.
When to use the Student’s t-test rule?
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. For example, suppose we have the following two samples: Sample 1 has a variance of 24.86 and sample 2 has a variance of 15.76.