Chapter 3
Tests on the variance
This chapter contains statistical tests on the variance of normal populations. In the one-sample case it is of interest whether the variance of a single population differs from some pre-specified value, where the mean value of the underlying Gaussian distribution may be known or unknown. SAS and R do not provide the user with ready to use procedures or functions for the resulting
-tests. For the two-sample cases it must be distinguished between independent and dependent samples. In the former case an F-test and in the latter case a t-test is appropriate. The SAS procedure proc ttest provides a way to calculate the test for the two-sided hypothesis. We additionally show how the test can be performed for the one-sided hypothesis. In R the function var.test calculates the test for all hypotheses. In SAS and R there is no convenient way to calculate the t-test for dependent samples and we provide code for it. For k-sample variance tests (Levene test, Bartlett test) please refer to Chapter 17 which covers ANOVA tests.
3.1 One-sample tests
This section deals with the question, if the variance differs from a predefined value.
3.1.1
-test on the variance (mean known)
| Description: | Tests if a population variance differs from a specific value . |
| Assumptions: ... |
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access