调查回复率计算器 — 公式
## How Cohen's d Measures Effect Size
Cohen's d quantifies the difference between two group means in standard deviation units, providing a measure of practical significance independent of sample size.
### Formula
**d = |Mean_1 - Mean_2| / SD_pooled**
Where **SD_pooled = sqrt((SD_1^2 + SD_2^2) / 2)**
### Interpretation
- Small effect: d = 0.2
- Medium effect: d = 0.5
- Large effect: d = 0.8
In education research, an effect size of 0.4 or higher is generally considered practically significant.
Cohen's d quantifies the difference between two group means in standard deviation units, providing a measure of practical significance independent of sample size.
### Formula
**d = |Mean_1 - Mean_2| / SD_pooled**
Where **SD_pooled = sqrt((SD_1^2 + SD_2^2) / 2)**
### Interpretation
- Small effect: d = 0.2
- Medium effect: d = 0.5
- Large effect: d = 0.8
In education research, an effect size of 0.4 or higher is generally considered practically significant.
计算示例
Treatment group scored mean 78 (SD = 10), control group scored mean 72 (SD = 12).
- Pooled SD = sqrt((100 + 144) / 2) = sqrt(122) = 11.05
- Mean difference: |78 - 72| = 6
- Cohen's d = 6 / 11.05 = 0.543
- Interpretation: Medium effect size