When running a Test of Equal Variance for Normal data, which test statistic is commonly used?

The F-test is commonly used as the test statistic for running a Test of Equal Variance for normally distributed data. This statistical test helps assess whether two or more groups have the same variance by comparing the ratio of variances from two samples. In the context of normally distributed data, the F-test is particularly appropriate because it is based on the properties of the normal distribution.

Bartlett's test, which is the answer you selected, is another method specifically designed to test the equality of variances across multiple groups. It is sensitive to departures from normality, which can impact the validity of its results. It is particularly useful when comparing variances from several independent samples that are assumed to be normally distributed.

Levene's test is typically used when the assumption of normality might be violated because it is more robust against non-normal data. It is based on the median and thus does not assume that the data follows a normal distribution, making it flexible in its application.

Standard deviation is a statistic that measures the amount of variation or dispersion in a set of values but is not a test statistic itself used for hypothesis testing.

In summary, while Bartlett's test is indeed used for testing equal variances, when specifically referring to the standard approach for normally distributed data,