In order to test the effectiveness of a drug called XZR designed to reduce cholesterol levels, the cholesterol levels of 9 heart patients ar measured before they are given the drug. The same 9 patients use \( X \) for two continuous months. After two months of continuous use, the cholesterol levels are measured again. The comparison of cholestero levels before versus after the administration of the drug is an example testing the difference between two Multiple Choice samples of equal variances samples of unequal variances

In this scenario, the cholesterol levels of the same group of patients are measured before and after the administration of the drug. This is considered a paired or related samples test, where the "before" and "after" measurements come from the same individuals. Hence, we are not comparing two independent samples, but rather evaluating the differences within matched pairs. The common mistake here is to think of it as independent samples. Remember, the same patients are involved in both measurements, which affects the type of statistical analysis employed. So, when faced with similar questions, it’s vital to look for the relationship between the data sets!