Contents
What does unequal variance mean?
For the unequal variance t test, the null hypothesis is that the two population means are the same but the two population variances may differ. The unequal variance t test reports a confidence interval for the difference between two means that is usable even if the standard deviations differ.
Can we compare medians?
When you compare medians, you should stop and ask yourself if you are interested in the difference in the medians of the two groups, or in the median difference between the observations in the two groups. The median difference is an interesting measure of effect size.
How do I know if I have equal or unequal variance?
1. Use the Variance Rule of Thumb. As a rule of thumb, if the ratio of the larger variance to the smaller variance is less than 4 then we can assume the variances are approximately equal and use the Student’s t-test.
How to calculate the variance of the three medians?
First choose a measure of the difference, something like the largest of the 3 medians minus the smallest of the 3 (or the variance of the 3 medians, or the MAD, etc.). Now compute your stat for the original data.
Is there a way to compare two variances in MINITAB?
Minitab will compare the two variances using the popular F-test method. If we only have summarized data (e.g. the sample sizes and sample variances or sample standard deviations), then the two variance test in Minitab will only provide an F-test.
How to compare the variance of two variables?
To compare the variances of two quantitative variables, the hypotheses of interest are: The last two alternatives are determined by how you arrange your ratio of the two sample statistics. We will rely on Minitab to conduct this test for us. Minitab offers three (3) different methods to test equal variances.
Why are sample sizes unequal in table 15.6?
Weighted and unweighted means will be explained using the data shown in Table 15.6. 4. Here, Diet and Exercise are confounded because 80 % of the subjects in the low-fat condition exercised as compared to 20 % of those in the high-fat condition. However, there is not complete confounding as there was with the data in Table 15.6.