# Should I use equal variances assumed or not assumed?

## Should I use equal variances assumed or not 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).

## How do you know if equal variances are assumed in SPSS?

There is a long equation used to determine which variance to use, but SPSS does this for you by running the Levene’s Test for Equality of Variances. If the variances are relatively equal, that is one sample variance is no larger than twice the size of the other, then you can assume equal variances.

Do t tests 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.

What does t-test assuming equal variances mean?

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.

### What statistic tells you if your assumptions of equal variance are correct?

Levene’s test ( Levene 1960) is used to test if k samples have equal variances. Equal variances across samples is called homogeneity of variance.

### How do I know if variances are equal?

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.

What are the assumptions of a two sample t test?

Two-sample t-test assumptions Data in each group must be obtained via a random sample from the population. Data in each group are normally distributed. Data values are continuous. The variances for the two independent groups are equal.

What is the difference between t-test equal variance and unequal variance?

If the variances are equal then the equal and unequal variances versions of the t-test will yield similar results (even when the sample sizes are unequal), although the equal variances version will have slightly better statistical power.

#### What is t test statistic in SPSS?

Test Statistic. The test statistic for an Independent Samples t Test is denoted t. There are actually two forms of the test statistic for this test, depending on whether or not equal variances are assumed. SPSS produces both forms of the test, so both forms of the test are described here.

#### How do you test for homogeneity of variance in SPSS?

Recall that the Independent Samples t Test requires the assumption of homogeneity of variance — i.e., both groups have the same variance. SPSS conveniently includes a test for the homogeneity of variance, called Levene’s Test, whenever you run an independent samples t test.

What is the test statistic for unequal variances?

Equal variances not assumed When the two independent samples are assumed to be drawn from populations with unequal variances (i.e., σ 12 ≠ σ 22), the test statistic t is computed as: t = x ¯ 1 − x ¯ 2 s 1 2 n 1 + s 2 2 n 2

What if the two samples do not have equal variance?

So, if the two samples do not have equal variance then it’s best to use the Welch’s t-test. But how do we determine if the two samples have equal variance? 1. Use the Variance Rule of Thumb.