Two-Way ANOVA Calculator

1. Collect observations grouped by two factors (A and B).
2. Create rows as FactorA,FactorB,Value.
3. Paste rows or upload a CSV file.
4. Set α and press Submit.
5. Review main effects and interaction p-values.
6. Download CSV/PDF for reporting and documentation.

1) What does a two-way ANOVA test?

It tests whether Factor A, Factor B, or their interaction changes the mean outcome. Interaction means the effect of one factor depends on the level of the other factor.

2) Do I need the same sample size in each cell?

Balanced data is ideal, but not required here. The calculator uses weighted sums of squares when cell sizes differ. Strong imbalance can make interpretation less stable.

3) Why does it say I need replication?

To estimate the error term, you need repeats inside at least some A×B cells. If every cell has only one value, the error degrees of freedom become zero.

4) How do I interpret the interaction p-value?

If interaction is significant, interpret cell or simple effects rather than only main effects. Plotting cell means often helps you see how Factor A and Factor B combine.

5) What assumptions should I check?

Independence, roughly normal residuals, and similar variances across cells. ANOVA is fairly robust to mild non-normality, but strong heteroscedasticity can affect results.

6) What if a cell is missing entirely?

Missing cells break the full factorial structure and the model becomes harder to interpret. Add data for missing combinations, or consider a different model that fits your design.

7) Can I use this for repeated-measures designs?

Not directly. Repeated measures need subject-level correlation handling and different error terms. Use a repeated-measures ANOVA or mixed-effects model for within-subject factors.