Run professional-grade statistical tests directly in your browser. No login. No data sent to servers. Instant F-statistic, p-value & plain-English interpretation tailored to your role.
Compare multiple independent groups — enter your data below.
Analyse main & interaction effects of two independent factors. (Balanced design — min 2 observations per cell)
Compare the same subjects across multiple conditions or time points.
Compare multiple groups across multiple dependent variables simultaneously.
If you need to compare the average performance of three or more groups, this ANOVA Calculator is built for you. ANOVA — Analysis of Variance — tests all groups simultaneously in a single, coherent framework without inflating error rates the way multiple t-tests would.
ANOVA answers a fundamental question: Are the differences between group means statistically significant, or could they simply be explained by random variation? It decomposes total variation into between-group (SSB) and within-group (SSW) components. If between-group variation greatly exceeds within-group variation, the F-statistic rises — indicating real, meaningful group differences.
Consider three teachers using different methods (lecture, flipped classroom, project-based). You collect exam scores from each class. ANOVA tells you whether the class average differences are real or just random student-level noise — via a formal hypothesis test with a null hypothesis (all means equal) and alternative (at least one differs).
All calculations run entirely in your browser via JavaScript. When you click Calculate:
Use ANOVA when you have a continuous outcome and a categorical grouping variable with three or more levels:
ANOVA compares the means of three or more groups to determine whether at least one group differs significantly. It is widely used in education, research, business, and science.
The F-statistic is the ratio of between-group mean square to within-group mean square. A high F paired with a low p-value suggests significant group differences.
The p-value is the probability of observing your F-statistic (or more extreme) if the null hypothesis were true. A p-value below 0.05 typically leads to rejecting the null hypothesis.
Yes — completely free, no account or login required. All four calculators are available at no cost, forever.
Not for One-Way ANOVA. For Two-Way ANOVA, a balanced design (equal observations per cell) is assumed for accurate interaction calculations.
ANOVA assumes: (1) independence of observations, (2) approximate normality within each group, and (3) homogeneity of variance across groups. Violations may affect reliability.
A complete beginner's guide to Analysis of Variance — concepts, formulas, and real-world examples.
Read More →When should you use ANOVA instead of a Student's T-Test? A practical decision guide.
Read More →Multivariate ANOVA demystified — when to use it and how to interpret the results.
Read More →7 common pitfalls when interpreting p-values and F-statistics that can invalidate your research.
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