When to use it
- •You have three or more independent groups.
- •Your outcome is continuous.
- •You want an omnibus test before looking at specific pairs.
Assumptions to check first
- •Independent observations across groups.
- •Approximately normal outcome within each group.
- •Homogeneity of variance (Welch's ANOVA is the fallback when this fails).
What to report
- •F with both degrees of freedom (between and within), and the exact p.
- •An effect size — η² or partial η².
- •Descriptives for every group.
- •Post-hoc comparisons with the correction used (Tukey, Bonferroni, etc.), but only if the omnibus test warrants them.
APA 7 example
Department had a significant effect on engagement, F(3, 196) = 7.82, p < .001, η² = .11. Tukey post-hoc comparisons showed Sales scored significantly lower than R&D (p = .002) and Marketing (p = .014).
Numbers are illustrative — the Advisor generates this sentence with your own results.
The mistake reviewers catch
A significant F tells you that some group differs — not which one. Jumping straight to pairwise t-tests without a correction is exactly the error ANOVA exists to prevent.
Run it on your own data
Paste or upload your dataset — nothing leaves your browser. The Analysis Advisor checks the assumptions above, runs anova, and drafts the APA Methods and Results text with your numbers in it.
Open the Analysis Advisor →Related analyses
Frequently asked questions
When should I use anova?
Do three or more groups differ on average? You have three or more independent groups.
What do I need to report for anova in APA 7?
F with both degrees of freedom (between and within), and the exact p. An effect size — η² or partial η². Descriptives for every group. Post-hoc comparisons with the correction used (Tukey, Bonferroni, etc.), but only if the omnibus test warrants them.
What is the most common mistake with anova?
A significant F tells you that some group differs — not which one. Jumping straight to pairwise t-tests without a correction is exactly the error ANOVA exists to prevent.