Which statistical test is appropriate for testing significant differences in means among three or more groups?

The correct choice is the ANOVA (Analysis of Variance) test, which is specifically designed to compare means across three or more independent groups. This statistical method assesses whether at least one group mean is statistically different from the others, helping to identify variations in effects among multiple groups.

Using ANOVA allows researchers to analyze the impact of one or more factors (independent variables) on a continuous outcome variable while controlling for type I error that could occur with multiple pairwise comparisons. If ANOVA indicates significant differences, post-hoc tests can be performed to determine which specific groups differ.

In contrast, the independent T test and paired T test are designed for comparing means between two groups. The independent T test is suitable when comparing different groups, while the paired T test applies to related groups, such as the same subjects measured at two time points. The Mann-Whitney U test is a non-parametric test used to compare differences between two independent groups without assuming a normal distribution, which also limits its application to only two groups rather than three or more.