Effect Size Calculator (Cohen's d) Formula
Understand the math behind the effect size calculator (cohen's d). Each variable explained with a worked example.
Formulas Used
Cohen's d
cohens_d = abs(mean1 - mean2) / pooled_sdPooled Standard Deviation
pooled_sd_out = pooled_sdMean Difference
mean_diff = abs(mean1 - mean2)Variables
| Variable | Description | Default |
|---|---|---|
mean1 | Group 1 Mean | 78 |
mean2 | Group 2 Mean | 72 |
sd1 | Group 1 Std Deviation | 10 |
sd2 | Group 2 Std Deviation | 12 |
pooled_sd | Derived value= sqrt((pow(sd1, 2) + pow(sd2, 2)) / 2) | calculated |
How It Works
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
In education research, an effect size of 0.4 or higher is generally considered practically significant.
Worked Example
Treatment group scored mean 78 (SD = 10), control group scored mean 72 (SD = 12).
mean1 = 78mean2 = 72sd1 = 10sd2 = 12
- 01Pooled SD = sqrt((100 + 144) / 2) = sqrt(122) = 11.05
- 02Mean difference: |78 - 72| = 6
- 03Cohen's d = 6 / 11.05 = 0.543
- 04Interpretation: Medium effect size
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