Effect Size (Cohen's d) Calculator
This calculator is designed for researchers and statisticians to compute the effect size (Cohen's d) for hypothesis testing. It helps determine the magnitude of difference between two groups.
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The Formula Explained
Cohen's d is calculated using the formula:
\[ d = \frac{\bar{X}_1 - \bar{X}_2}{s} \]
where \(\bar{X}_1\) and \(\bar{X}_2\) are the means of the two groups, and \(s\) is the pooled standard deviation.
Glossary of Variables
- Mean of Group 1: The average of the first group.
- Mean of Group 2: The average of the second group.
- Standard Deviation: A measure of the amount of variation or dispersion of a set of values.
- Cohen's d: The effect size calculated.
How It Works: A Step-by-Step Example
Suppose Group 1 has a mean of 5 and Group 2 has a mean of 3. If the standard deviation is 1, then Cohen's d is calculated as:
\[ d = \frac{5 - 3}{1} = 2 \]
This indicates a large effect size.
Frequently Asked Questions (FAQ)
What is Cohen's d?
Cohen's d is a measure of effect size used to indicate the standardised difference between two means.
How do I interpret Cohen's d?
Typically, 0.2 is considered a small effect size, 0.5 a medium effect size, and 0.8 a large effect size.
Can Cohen's d be negative?
Yes, Cohen's d can be negative if the second group mean is higher than the first.
Why is effect size important?
Effect size quantifies the size of the difference and helps interpret the practical significance of results.
What are the limitations of Cohen's d?
Cohen's d assumes normally distributed data and equal variances within groups.