I need to test for equal variance. I tried to read up and it mentioned there are a few tests I can use to test for equality of variance such as F Test (F ratio?), Levene Test, Bartlett Test etc.
I was wondering if there is a qualitative method of telling whether there is equal variance by using the SD and the mean of the two data sets (both normally distributed) My lecturer was saying I can assume equal variance by just looking the mean and the SD?
I do not know how to tell… can anyone help?
Note that all the tests for equal variances are rule out tests. They test the null hypothesis that the 2 variances (standard deviations) are equal, so if you reject the null hypothesis then you can be fairly sure that they are not equal, but if you get a non-significant result that does not mean that they are equal, they could be equal or you may just not have enough power to find the difference.
The rules of thumb are often more useful because if the variances are not equal, but still similar then your other tests are still reasonable.
What is the most important is an understanding of the science that produces the data and the question of interest. There are cases where the distributions have different enough variance that you would not want to use methods that assume equal variances, but many of the samples from the distributions would not reject the equal variances
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