FPGEE for National Association of Boards of Pharmacy (NABP) Practice Exam 2026 - Free NABP Practice Questions and Study Guide

In an ANOVA (Analysis of Variance) test, the primary objective is to compare the means of three or more groups to determine if there are statistically significant differences among them. This method is particularly useful when dealing with multiple groups, as it helps to assess whether at least one group mean is different from the others based on the data collected.

The reasoning behind using ANOVA is that it allows researchers to evaluate the effect of a categorical independent variable on a continuous dependent variable across multiple levels, all in one go rather than conducting multiple t-tests, which would risk inflating the Type I error rate. By analyzing the variation within and between the groups, ANOVA helps to identify if any observed differences in sample means are likely to reflect true population differences or if they occurred by chance.

The other choices do not align with the specific purpose of an ANOVA test. For instance, comparing one mean or two proportions does not require ANOVA, as simpler statistical tests such as a t-test are more appropriate for such comparisons. Evaluating variances of two categories pertains to other tests specific to variance analysis, not ANOVA. Thus, the correct focus of an ANOVA test is indeed on means of three or more groups.