Cohen's d
Cohen's d is a standardized effect-size measure expressing the difference between two group means in standard-deviation units, commonly using the pooled standard deviation.
Statistics Slam Dunk
Cohen's d is a standardized effect-size measure expressing the difference between two group means relative to a standard deviation, commonly the pooled standard deviation.
- How it is used
- Complements t-tests by quantifying the magnitude of mean differences for two groups with continuous outcomes.
- How deep it goes
- Defines pooled-standard-deviation scaling, output ratings, sign direction, confidence intervals, and R calls without deriving the statistic formally.
- Examples
- Compares home and road fouls and free throws, then contrasts Gini coefficients for winning and losing NBA teams.
- What you can do after
- Apply it via the effsize or effectsize package to quantify and interpret two-group mean differences alongside t-tests.
Effective Data Analysis
Cohen's d is a standardized effect-size measure expressing the difference between two means in standard-deviation units.
- How it is used
- Checks whether a difference between group means is substantial enough to consider alongside statistical significance.
- How deep it goes
- Defines its purpose as an effect-size measure but stops short of a formula or worked Cohen’s d calculation.
- Examples
- Uses test-score differences and conversion-rate gains to illustrate why practical importance depends on context.
- What you can do after
- Evaluate/understand whether a statistically significant difference merits further consideration, without relying on significance alone.
Related concepts
- effect sizemeasures · An effect size is a quantitative measure of the magnitude of a difference, association, relationship, or other observed phenomenon, independent of statistical significance.
- Cramer's Vcontrasts with · Cramer's V is a normalized, directionless measure of association strength between categorical variables in a contingency table, ranging from 0 to 1.
- Hedges' gcontrasts with · Hedges' g is a bias-corrected standardized effect-size measure for the difference between two group means.
- practical importancemeasures · Practical importance is the real-world significance of an effect, assessed by whether its magnitude meaningfully affects outcomes or decisions.
- t-testcontrasts with · A t-test is a statistical hypothesis test that uses a t-distributed statistic to assess a mean or difference in means under specified assumptions.
- Glass's deltacontrasts with · Glass's delta is a standardized mean difference obtained by dividing the difference between two means by the standard deviation of a reference group.
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