How deeply does Effective Data Analysis cover Cohen's d?

Defines its purpose as an effect-size measure but stops short of a formula or worked Cohen’s d calculation.

Cohen's d

Cohen's d is a standardized effect-size measure expressing the difference between two means in standard-deviation units.

Cohen’s d expresses the difference between two group means in standard-deviation units. It is an effect-size measure: it helps assess the magnitude of a difference, rather than only whether a statistical test finds one. section 4.2.1

With large samples, parametric tests can find statistically significant differences between nearly identical means. Cohen’s d offers a magnitude check that is not affected by sample size. Pair it with a minimum difference that matters in the domain, rather than treating significance alone as a recommendation. section 4.2.1

Deciding what matters

An average test-score difference of 0.5% may not matter, while a 0.2% increase in conversion rate could have meaningful revenue implications. Effect size informs that discussion; domain knowledge and a confidence interval help assess the difference against a chosen threshold. section 4.2.1

How Effective Data Analysis covers it

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Statistics Slam DunkCohen'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.

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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.

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.