Shall you use the test for equal or unequal variances? If you have equal numbers of data points, or the numbers are nearly the same, then you should be able to safely use the two-sample test for equal variances.
Contents
- 1 Should I use equal or unequal variance t test?
- 2 When should you use equal variance?
- 3 What does equal or unequal variance mean?
- 4 Which t test is equal or unequal variance?
- 5 What does equal variance mean in t-test?
- 6 What does equal variances mean?
- 7 How do you know if variances are equal?
- 8 What is the difference between a paired and unpaired t-test?
- 9 What does AP value of less than 0.05 mean?
- 10 Can you run at test with unequal sample sizes?
- 11 Is Welch test non parametric?
- 12 What is a t-test two-sample assuming unequal variances?
- 13 When would you use a two-tailed test?
- 14 What kind of t-test should I use?
Should I use equal or unequal variance t test?
Welch’s t-test: Assumes that both groups of data are sampled from populations that follow a normal distribution, but it does not assume that those two populations have the same variance. So, if the two samples do not have equal variance then it’s best to use the Welch’s t-test.
When should you use equal 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.
What does equal or unequal variance mean?
For the unequal variance t test, the null hypothesis is that the two population means are the same but the two population variances may differ. The unequal variance t test reports a confidence interval for the difference between two means that is usable even if the standard deviations differ.
Which t test is equal or unequal variance?
In statistics, Welch’s t-test, or unequal variances t-test, is a two-sample location test which is used to test the hypothesis that two populations have equal means.
What does equal variance mean in t-test?
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 does equal variances mean?
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.
How do you know if variances are equal?
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.
What is the difference between a paired and unpaired t-test?
A paired t-test is designed to compare the means of the same group or item under two separate scenarios. An unpaired t-test compares the means of two independent or unrelated groups. In an unpaired t-test, the variance between groups is assumed to be equal.
What does AP value of less than 0.05 mean?
A p-value less than 0.05 (typically ≤ 0.05) is statistically significant. It indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null is correct (and the results are random). Therefore, we reject the null hypothesis, and accept the alternative hypothesis.
Can you run at 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.
Is Welch test non parametric?
Abstract. Welch t-test is the parametric test for comparing means between two independent groups without assuming equal population variances. This statistic is robust for testing the mean equality when homogeneity assumption is not satisfied, but Welch test is not always robust.
What is a t-test two-sample assuming unequal variances?
This tool executes a two-sample student’s t-Test on data sets from two independent populations with unequal variances. This test can be either two-tailed or one-tailed contingent upon if we are testing that the two population means are different or if one is greater than the other.
When would you use a two-tailed test?
A two-tailed test is appropriate if you want to determine if there is any difference between the groups you are comparing. For instance, if you want to see if Group A scored higher or lower than Group B, then you would want to use a two-tailed test.
What kind of t-test should I use?
If you are studying two groups, use a two-sample t-test. If you want to know only whether a difference exists, use a two-tailed test. If you want to know if one group mean is greater or less than the other, use a left-tailed or right-tailed one-tailed test.
