One-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
Choose one factor and continuous outcomes. Use classical ANOVA with Tukey or Bonferroni; use Welch with Games–Howell for unequal variances. Incompatible combinations are rejected.
Variables
| Control | Input |
|---|---|
| Analysis variables | Select variables |
| Group Variable | Select one variable |
Analysis settings
| Parameter | Choices | Default |
|---|---|---|
| ANOVA method | Classical ANOVA, Welch ANOVA | classic |
| Post hoc comparisons | None, Tukey, Bonferroni, Games–Howell | none |
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.