Which of the following are common post-hoc tests?

Which of the following are common post-hoc tests?

• A. Tukey, Bonferroni, Scheffe
• B. Tukey
• C. Bonferroni
• D. Scheffe

Answer: (A)

After an ANOVA shows a significant difference among group means, you need to pinpoint which specific group comparisons are driving that effect. Post-hoc tests provide those multiple pairwise comparisons while keeping the overall chance of a false positive (familywise error) under control. The common tools for this purpose include Tukey's Honestly Significant Difference, Bonferroni-adjusted tests, and Scheffe's method. Tukey's test is designed for all pairwise comparisons and uses a uniform threshold that maintains the familywise error rate across all pairs when variances are equal. Bonferroni is straightforward: you divide the desired alpha by the number of comparisons, offering a conservative guard against false positives, especially when many groups are involved. Scheffé's method is flexible and quite conservative, allowing testing of any linear contrasts—not just simple pairs—while still controlling the familywise error rate. Because these three are widely taught and used as standard post-hoc options, listing them together reflects the typical toolkit researchers rely on after a significant ANOVA. If you only name one, you’re omitting other common approaches that are also appropriate in different situations.

After an ANOVA shows a significant difference among group means, you need to pinpoint which specific group comparisons are driving that effect. Post-hoc tests provide those multiple pairwise comparisons while keeping the overall chance of a false positive (familywise error) under control.

The common tools for this purpose include Tukey's Honestly Significant Difference, Bonferroni-adjusted tests, and Scheffe's method. Tukey's test is designed for all pairwise comparisons and uses a uniform threshold that maintains the familywise error rate across all pairs when variances are equal. Bonferroni is straightforward: you divide the desired alpha by the number of comparisons, offering a conservative guard against false positives, especially when many groups are involved. Scheffé's method is flexible and quite conservative, allowing testing of any linear contrasts—not just simple pairs—while still controlling the familywise error rate.

Because these three are widely taught and used as standard post-hoc options, listing them together reflects the typical toolkit researchers rely on after a significant ANOVA. If you only name one, you’re omitting other common approaches that are also appropriate in different situations.