Effect Size Calculator

Calculate effect sizes for t-tests, ANOVA, regression, and chi-square. Get magnitude interpretation (small/medium/large) with an APA-ready citation.

Effect Size Measure

Select the effect size measure that matches your statistical test.

Mean of Group 1 (M₁)

Mean of Group 2 (M₂)

SD of Group 1 (SD₁)

SD of Group 2 (SD₂)

Sample Size Group 1 (n₁)

Sample Size Group 2 (n₂)

How to Use This Calculator

1. Select your effect size measure: Choose the measure that matches your statistical test. Use Cohen's d for independent t-tests, eta-squared or partial eta-squared for ANOVA, R-squared for regression, odds ratio for 2x2 tables, or Cramér's V for chi-square tests.

2. Enter your values: Input the required statistics from your SPSS, R, or other software output. For Cohen's d, you need means, standard deviations, and sample sizes for both groups. For ANOVA effect sizes, you need the F-value and degrees of freedom.

3. Calculate: The calculator computes the effect size and classifies it as small, medium, or large using Cohen's (1988) conventions. Additional related values are shown for reference.

4. Report in your thesis: APA 7th edition requires reporting effect sizes alongside significance tests. Copy the generated APA citation directly into your results chapter.

About Effect Sizes

Effect sizes measure the practical significance of a finding, beyond just statistical significance (p-value). A result can be statistically significant but have a tiny effect size, meaning it has little practical importance. APA 7th edition requires reporting effect sizes in all quantitative research.

Cohen's d (t-tests)

Measures the standardized difference between two group means. Calculated as the mean difference divided by the pooled standard deviation. Cohen's (1988) benchmarks: small = 0.2, medium = 0.5, large = 0.8.

Eta-squared and Partial Eta-squared (ANOVA)

Eta-squared (η²) represents the proportion of total variance explained by the factor. Partial eta-squared (ηp²) represents the proportion of variance explained by the factor after accounting for other factors. SPSS reports partial eta-squared by default. Cohen's benchmarks: small = 0.01, medium = 0.06, large = 0.14.

R-squared (Regression)

The coefficient of determination (R²) represents the proportion of variance in the dependent variable explained by the predictor(s). Cohen's benchmarks: small = 0.02, medium = 0.13, large = 0.26.

Odds Ratio (Logistic Regression / 2x2 Tables)

The odds ratio (OR) compares the odds of an outcome between two groups. An OR of 1 means no difference. OR greater than 1 means higher odds in the exposed group. The calculator also provides 95% confidence intervals.

Cramér's V (Chi-Square)

Measures the strength of association between two categorical variables. Ranges from 0 (no association) to 1 (perfect association). Cohen's benchmarks: small = 0.1, medium = 0.3, large = 0.5.