Standardised effect sizes are important in data analysis because they report the magnitude of an effect, regardless of sample size.
These are conventional benchmarks commonly used in psychology for interpreting effect sizes. Take a screenshot, or add to your notes for a compact and simple guide.
Important Note: Always interpret effect sizes within the context of your research field. Ranges may vary.
| Size of Effect | Cohen’s d | Pearson’s r | Cohen’s W | R² (Regression) |
|---|---|---|---|---|
| Negligible | < 0.20 | < 0.10 | < 0.10 | < 0.02 |
| Small | 0.20 – 0.49 | 0.10 – 0.29 | 0.10 – 0.29 | 0.02 – 0.13 |
| Moderate | 0.50 – 0.79 | 0.30 – 0.49 | 0.30 – 0.49 | 0.13 – 0.25 |
| Large | ≥ 0.80 | ≥ 0.50 | ≥ 0.50 | ≥ 0.26 |
