Cohen's d effect size calculator

Paste the raw data of two groups, or their mean, standard deviation and size, to see how large the difference between them is in standard deviation units. You get Cohen's d, the small-sample Hedges' g, Glass's Δ and a rough size label.

Raw data: the values separated by commas or spaces. Summary: mean, standard deviation and size, for example 24.5, 4.2, 30.
Same format as group 1. Glass's Δ uses this group's standard deviation.
Cohen's d2.01246
Hedges' g1.90269
Size (Cohen's benchmarks)
Large (0.8 or more)
95% interval of d (approximate)
0.809735 – 3.21519
Glass's Δ
2.25
Pooled standard deviation
2.23607
Difference of means (1 − 2)
4.5
Group 1: mean, SD, n
26.5, 2.44949, 8
Group 2: mean, SD, n
22, 2, 8

Runs in your browser: nothing you enter is sent anywhere.

How to use it

  1. Choose raw data or summary statistics.
  2. Enter group 1 and group 2. In summary mode type the mean, standard deviation and size, separated by commas.
  3. Read d, g, the size label and the interval.

Formulas

  • Pooled SD: s_p = √(((n₁ − 1)s₁² + (n₂ − 1)s₂²) ÷ (n₁ + n₂ − 2))
  • Cohen’s d = (mean₁ − mean₂) ÷ s_p
  • Hedges’ g = d × (1 − 3 ÷ (4(n₁ + n₂) − 9))
  • Glass’s Δ = (mean₁ − mean₂) ÷ s₂
  • 95% interval: d ± 1.96 × √((n₁ + n₂)/(n₁n₂) + d²/(2(n₁ + n₂))), a normal approximation

Raw data use the sample standard deviation (dividing by n − 1).

Worked example

Group 1: 2, 4, 6 (mean 4, SD 2). Group 2: 1, 3, 5 (mean 3, SD 2).

s_p = √((2 × 4 + 2 × 4) ÷ 4) = 2, so d = (4 − 3) ÷ 2 = 0.5, a medium effect. Hedges’ correction is 1 − 3 ÷ (4 × 6 − 9) = 1 − 3/15 = 0.8, so g = 0.4. Glass’s Δ = 1 ÷ 2 = 0.5.

Tips and common mistakes

  • The sign shows direction: d is negative when group 1 has the smaller mean.
  • An effect size says how big a difference is, not whether it is statistically significant; report it next to the p-value of a t-test.
  • Use the standard deviation, not the standard error, in summary mode. If a paper gives SE, multiply it by √n first.

Frequently asked questions

What counts as a small, medium or large effect?

Cohen suggested 0.2 as small, 0.5 as medium and 0.8 as large. He meant them as rough guides when nothing better is known; what matters in practice depends on the field.

What is the difference between Cohen's d and Hedges' g?

Both divide the difference of means by the pooled standard deviation. Cohen's d is slightly too large in small samples; Hedges' g multiplies it by 1 − 3/(4(n₁ + n₂) − 9) to remove most of that bias. With 20 or more per group they are nearly equal.

When should I use Glass's Δ?

When the treatment may change the spread as well as the mean. Glass's Δ divides by the control group's standard deviation only, so put the control group in the second box.

Can I use it for paired data?

This calculator treats the groups as independent. For paired data, one common choice is the mean difference divided by the standard deviation of the differences, which is not the same number.

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