Which stat test is designed to compare two means in parametric data?

• A. T-test
• B. ANOVA
• C. Mann-Whitney U Test
• D. Chi-square

Answer: (A)

When you want to compare two means in data that meet parametric assumptions (continuous, normally distributed, with similar variances), the t-test is the right choice. It asks whether the observed difference between the two group means is larger than what would be expected by chance, taking into account the data’s variability and the sample size. There are two forms: independent-samples t-test for two different groups, and paired t-test for measurements from the same subjects (before/after or matched pairs). The t-statistic is the difference in means divided by the standard error, and its significance is assessed against the t-distribution.

In contrast, analysis of variance compares three or more means; the Mann-Whitney U test is the nonparametric alternative that compares distributions or medians when data aren’t normally distributed; and the Chi-square test analyzes frequencies in categories rather than means.