Effect Size Visualizer
Shows what different effect sizes (e.g. Cohen's d) actually look like as overlapping distributions.
What it does
- Displays two group distributions with separation controlled by the effect size
- Adjust Cohen's d to see how overlap changes
- Builds intuition for practical significance vs statistical significance
Key concepts illustrated
- A "small" effect (d = 0.2) has extensive overlap between groups
- A "medium" effect (d = 0.5) still has substantial overlap
- A "large" effect (d = 0.8) shows clearer separation
- Statistical significance is not the same as practical importance
Cohen's d benchmarks
| d | Label |
|---|---|
| 0.2 | Small |
| 0.5 | Medium |
| 0.8 | Large |
This is a teaching tool for building intuition about effect sizes.
A UniversalChatBot is available for discussion.