Which statistical test is appropriate when comparing two or more means?

When comparing two or more means, the most appropriate statistical test is ANOVA, which stands for Analysis of Variance. ANOVA is specifically designed to evaluate whether there are any statistically significant differences between the means of three or more independent groups. It assesses the variability within each group relative to the variability between the groups, allowing researchers to determine if at least one group mean is different from the others.

In contrast, while the T test is suitable for comparing the means of two groups, it does not extend to more than two groups effectively. MANOVA, or Multivariate Analysis of Variance, deals with multiple dependent variables but is not the primary choice when simply comparing group means. Chi Square is primarily used for categorical data to assess how likely it is that an observed distribution is due to chance, rather than comparing means.

Given these distinctions, ANOVA stands out as the right choice when the goal is to understand differences across multiple means simultaneously.