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Cohen's D Formula:
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Cohen's D is a standardized effect size measure that quantifies the difference between two means in terms of standard deviation units. It provides a scale-free measure of effect magnitude that is comparable across different studies and measurements.
The calculator uses the Cohen's D formula:
Where:
Explanation: The formula calculates the standardized difference between two means by dividing their difference by the pooled standard deviation, providing a unitless measure of effect size.
Details: Cohen's D is crucial for quantifying the magnitude of differences between groups in research studies, meta-analyses, and statistical power analysis. It helps researchers determine the practical significance of their findings beyond statistical significance.
Tips: Enter the means for both groups and the pooled standard deviation. All values must be valid (SD_pooled > 0). The result is a unitless measure of effect size.
Q1: What are the typical interpretations of Cohen's D values?
A: Small effect: d ≈ 0.2, Medium effect: d ≈ 0.5, Large effect: d ≈ 0.8. These are general guidelines and may vary by field.
Q2: How is pooled standard deviation calculated?
A: SD_pooled = √[((n1-1)*SD1² + (n2-1)*SD2²) / (n1+n2-2)], where n1 and n2 are sample sizes, SD1 and SD2 are standard deviations.
Q3: When should Cohen's D be used?
A: When comparing means between two independent groups in experimental and observational studies to quantify effect size.
Q4: Are there limitations to Cohen's D?
A: It assumes normal distributions and equal variances. May be less accurate with small sample sizes or non-normal distributions.
Q5: How does Cohen's D relate to statistical significance?
A: While p-values indicate statistical significance, Cohen's D quantifies the magnitude of the effect, providing information about practical significance.