One-Way vs. Two-Way ANOVA: Key Differences & When to Use Each
One-Way ANOVA tests one factor across multiple groups; Two-Way ANOVA tests two factors plus their interaction.
Researchers often mix them up because spreadsheet menus list both under “ANOVA,” tempting a quick click without checking study design.
Key Differences
One-Way: single categorical predictor. Two-Way: two predictors + interaction term. Output: extra F-ratio and p-value for interaction effect.
Which One Should You Choose?
Use One-Way when only one variable (e.g., fertilizer type) explains crop yield. Choose Two-Way when a second variable (e.g., watering schedule) and their combo might matter.
Examples and Daily Life
Marketing: One-Way compares click-through rates across email headlines; Two-Way adds send-time to see if headline success changes by morning vs. evening.
Can Two-Way ANOVA be run without interaction?
Yes, but you’ll miss testing synergy between factors.
Is One-Way just a subset of Two-Way?
Conceptually yes—drop one factor and interaction to get One-Way.