How does ANOVA differ from t-tests in comparing means?
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ANOVA differs from t-tests in that it can compare means across three or more groups simultaneously, while t-tests are typically used for comparing the means of two groups; additionally, ANOVA assesses overall differences without specifying which groups differ, whereas t-tests provide direct pairwise comparisons.
ANOVA is used to compare the means of three or more groups at once, while t-tests are designed for comparing the means of just two groups. Basically, ANOVA helps determine if there are any significant differences among multiple groups, whereas t-tests focus on differences between just two groups.