Two-Way ANOVA
Purpose
Compare means across independent groups and, when applicable, examine interactions.
Data and assumptions
These are independent-group analyses, not repeated-measures models. Review within-group residuals, variance assumptions, cell sizes and empty cells.
Configure this method
Specify two factors; the model contains both main effects and their interaction. Type II and III sums of squares address different hypotheses in unbalanced designs. Simple effects use pooled model error with Holm adjustment.
Variables
| Control | Input |
|---|---|
| Analysis variables | Select variables |
| Group Variable | Select one variable |
| Second grouping variable | Select one variable |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| Sum-of-squares type | Type III, Type II | 3 |
| Test simple effects | Set as needed | Disabled |
Analysis parameters remain visible in the main configuration area. Advanced formatting contains only the table title and numeric decimals. Methods that calculate intervals also show the significance level; 0.05 corresponds to 95% intervals.
Read the results
A significant overall F does not imply that every pair differs. Use a suitable post-hoc procedure to locate differences and interpret adjusted p-values.
Workflow and exports
- Upload the dataset and choose the method from the sidebar or search.
- Select the variables above, set the design-specific options, then run the analysis.
- Inspect the paper-style result. Reconfigure from the result area, or open raw output for diagnostics and sample details.
- Rename and keep result tabs as needed. Export Word, Excel, CSV or TXT; batch export can include the selected AI interpretation. Word retains figures. AI text should be checked against the estimates.