## Which t-test is equal or unequal variance?

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.

## Can you use t-test for unequal sample sizes?

If sample sizes in both conditions are equal, the t-test is very robust against unequal variances. If sample sizes are unequal, unequal variances can influence the Type 1 error rate of the t-test by either increasing or decreasing the Type 1 error rate from the nominal (often 0.05) alpha level.

**What is a two-sample unequal variance t-test?**

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 is 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.

### How do you find the degrees of freedom for an unequal variance?

To calculate degrees of freedom for ANOVA:

- Subtract 1 from the number of groups to find degrees of freedom between groups.
- Subtract the number of groups from the total number of subjects to find degrees of freedom within groups.
- Subtract 1 from the total number of subjects (values) to find total degrees of freedom.

**Why are unequal sample sizes a problem?**

Problems with Unequal Sample Sizes Unequal sample sizes can lead to: Unequal variances between samples, which affects the assumption of equal variances in tests like ANOVA. Having both unequal sample sizes and variances dramatically affects statistical power and Type I error rates (Rusticus & Lovato, 2014).

## In which two ways does the Welch t-test differ from the Student t-test?

The most important difference between Student’s t-test and Welch’s t-test, and indeed the main reason Welch’s t-test was developed, is when both the variances and the sample sizes differ between groups, the t-value, degrees of freedom, and p-value all differ between Student’s t-test and Welch’s t-test.

## How do you find degrees of freedom for t-test?

The p-value, corresponding to the absolute value of the t-test statistics (|t|), is computed for the degrees of freedom (df): df = n – 1 ….One sample t-test formula

- m is the sample mean.
- n is the sample size.
- s is the sample standard deviation with n−1 degrees of freedom.
- μ is the theoretical mean.

**What is the degree of freedom for two sample t-test?**

The degrees of freedom is the smaller of (6 – 1) and (9 – 1), or 5. A 90 percent confidence interval is equivalent to an alpha level of 0.10, which is then halved to give 0.05. According to Table 3 in “Statistics Tables,” the critical value for t .05,5 is 2.015.