An important consequence of this assumption is that tests of difference in location (like a permutation t-test) require equal variance.

Levene's test may also be used as a main test, for answering a stand-alone question whether two sub-samples in a given population have equal or different variances.

The assumption of equal variance is valid when the errors all belong to the same distribution.

By the result above, any unbiased estimator whose expectation is has variance greater than or equal to .

Usually, the assumption that the controls have equal variance in a plate holds.

The bimodality index assumes that the distribution is a sum of two normal distributions with equal variances but differing means.

The Laplace distribution has a variance equal to .

The parameters have been chosen to result in a variance equal to 1 in each case.

In cases where the assumption of equal variances was found to be unreasonable an approximate version of the two sample t test was adopted.

The t-test provides an exact test for the equality of the means of two normal populations with unknown, but equal, variances.