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

The statistical test that assesses the sizes and significance of differences between two means is the t-test. This test is specifically designed to determine if there is a statistically significant difference between the means of two groups, which can be either independent (unpaired t-test) or related (paired t-test). The t-test calculates a t-value based on the sample data and compares it to a critical value from the t-distribution to ascertain the likelihood of observing such a difference by chance.

The t-test is particularly useful when the sample sizes are small and the population standard deviations are unknown, making it a common choice for many practical applications in research and statistics involving comparisons of two groups.

In contrast, the chi-square test is used for categorical data to assess how likely it is that an observed distribution is due to chance. The F-test, on the other hand, is typically used to compare variances between two or more groups and is a precursor to ANOVA, which is used to compare means across three or more groups. Thus, while other tests focus on different aspects of data analysis, the t-test directly addresses the comparison of two means, making it the correct answer in this context.