The correct answer is: A. To compare more than two population means
An F-test is a statistical test that is used to compare the variances of two or more populations. It can be used to test the hypothesis that the variances of two populations are equal, or to test the hypothesis that the means of two populations are equal.
The F-test is not appropriate for comparing more than two population means. This is because the F-test is based on the assumption that the variances of the populations are equal. If the variances of the populations are not equal, then the F-test will not be accurate.
In order to compare more than two population means, a different type of test should be used, such as a one-way ANOVA or a multiple comparison test.
Here is a brief explanation of each option:
- Option A: To compare more than two population means. This is the only option that is not appropriate for an F-test. As explained above, the F-test is not appropriate for comparing more than two population means.
- Option B: To test the hypothesis about a single population variance. This is a valid use for an F-test. The F-test can be used to test the hypothesis that the variance of a population is equal to a specified value.
- Option C: To test the hypothesis about two population variances. This is also a valid use for an F-test. The F-test can be used to test the hypothesis that the variances of two populations are equal.
- Option D: To study about randomised block design. This is not a valid use for an F-test. The F-test is not a statistical test that is used to study about randomised block design.