Effect Size Calculator

Real-time calculation of Cohen's d, Pearson's r, Eta-squared, Odds Ratio, R², Cramer's V, and more

Real-time Calculations
10+ Effect Size Measures
Interpretation Guides
Calculation History
Export Results
Statistical Comparisons
Responsive Design
Professional Reporting

Cohen's d Calculator (Standardized Mean Difference)

Cohen's d Effect Size
0.85
Interpretation: Large effect size Large
Interpretation Guide

Small: d ≈ 0.2 | Medium: d ≈ 0.5 | Large: d ≥ 0.8

Cohen's d measures the difference between two means in standard deviation units.

Pearson's r Calculator (Correlation Coefficient)

Enter value between -1 and 1
Pearson's r Effect Size
0.65
Interpretation: Large positive correlation Large
Interpretation Guide

Small: r ≈ 0.1 | Medium: r ≈ 0.3 | Large: r ≥ 0.5

Pearson's r measures the strength and direction of linear relationship between two variables.

Eta-squared (η²) Calculator (ANOVA Effect Size)

Eta-squared (η²) Effect Size
0.42
Interpretation: Large effect size Large
Interpretation Guide

Small: η² ≈ 0.01 | Medium: η² ≈ 0.06 | Large: η² ≥ 0.14

Eta-squared represents the proportion of variance in the dependent variable explained by the independent variable.

Effect Size Comparison

Measure Value Magnitude
Cohen's d 0.85 Large
Pearson's r 0.65 Large
Eta-squared 0.42 Large
Odds Ratio 2.50 Medium
R-squared 0.35 Medium

Calculation History

Cohen's d
Group comparison
0.85
Just now
Pearson's r
Correlation analysis
0.65
Just now
Eta-squared
ANOVA result
0.42
Just now

Quick Calculators

Click any button to open the specific calculator with pre-filled example data.

How to Use the Effect Size Calculator: A Comprehensive Guide

Effect sizes are crucial statistical measures that quantify the magnitude of a relationship or difference between variables. Unlike p-values, which only tell you if an effect exists, effect sizes tell you how large that effect is. Our Effect Size Calculator provides real-time calculations for the most common effect size measures used in research and data analysis.

Key Functionalities of Our Tool:
Step-by-Step Usage Guide:
1. Select Your Calculator

Choose from Cohen's d for mean differences, Pearson's r for correlations, Eta-squared for ANOVA results, or other specialized calculators.

2. Input Your Data

Enter your statistical values in the appropriate fields. The tool includes example data to help you get started.

3. Review Real-time Results

As you type, the calculator updates results instantly. The interpretation section helps you understand the magnitude.

4. Compare & Export

Use the comparison table to view all your effect sizes together. Export results for your reports or presentations.

Why Effect Size Matters in Research:

Effect size is increasingly recognized as an essential complement to statistical significance testing. While p-values can be influenced by sample size, effect sizes provide a standardized measure of practical significance. Our tool helps researchers, students, and analysts quickly compute and interpret these crucial statistics.

Pro Tip:

When reporting research results, always include both statistical significance (p-values) and effect sizes. This provides a more complete picture of your findings and helps readers understand the practical importance of your results.

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