If Levene’s test indicates that the variances are equal across the two groups (i.e., p-value large), you will rely on the first row of output, Equal variances assumed, when you look at the results for the actual Independent Samples t Test (under the heading t-test for Equality of Means). If Levene’s test indicates that the variances are not
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t-Tests for Equal and Unequal Variances. You’ll notice that Excel has two forms of the two-sample t-test. One that assumes equal variances and the other that assumes unequal variances. Variances and the closely related standard deviation are measures of variability. All t-tests assume you obtained data from normally distributed populations.
2 Answers. Sorted by: 3. You have one big problem with the F-test for equality of variance, and two problems with naive testing for equality of variance in time series: 1) it's very sensitive to deviations from normality. This means that often things like Levene or Browne-Forsythe type tests (along with several others) are suggested instead.
Normality is tested with the Shapiro-Wilk’s test and equality of the variance is tested with Levene’s test. For our example, both tests yield non-significant -values. The -values of the Shapiro-Wilk’s tests are computed under the assumption that the drp scores (in general the dependent variables) grouped according to their condition are

This is a test for the null hypothesis that 2 independent samples have identical average (expected) values. This test assumes that the populations have identical variances by default. Parameters: a, barray_like. The arrays must have the same shape, except in the dimension corresponding to axis (the first, by default).

However, if you're doing this in order to decide whether to assume equal variance in (say) one-way ANOVA, you're generally better not to assume it (though if the sample sizes are equal, ANOVA isn't very sensitive to unequal variances in any case). The most straightforward generalization to k 2 k > 2 samples of the F-ratio test for two variances
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how to test for equal variance