Which metrics are used to measure effect size?

Which metrics are used to measure effect size?

• A. Eta squared and Cohen's d
• B. Mean difference
• C. P-values
• D. Confidence intervals

Answer: (A)

Effect size tells you how large the observed effect is, not just whether it’s statistically significant. Cohen’s d measures the difference between two group means in standard deviation units, making the magnitude comparable across studies and scales. Eta squared represents the proportion of the total variance in the outcome that is explained by the grouping factor, giving a sense of how much of the variability the factor accounts for in an ANOVA context. These are standard ways to express magnitude across different designs: Cohen’s d for two-group comparisons and eta squared for variance explained in ANOVA. The other options don’t directly quantify magnitude in a standardized way. A mean difference is a raw difference that isn’t standardized, p-values tell you about statistical significance under a null hypothesis, and confidence intervals convey precision around an estimate but are not a single measure of effect size themselves.

Effect size tells you how large the observed effect is, not just whether it’s statistically significant. Cohen’s d measures the difference between two group means in standard deviation units, making the magnitude comparable across studies and scales. Eta squared represents the proportion of the total variance in the outcome that is explained by the grouping factor, giving a sense of how much of the variability the factor accounts for in an ANOVA context. These are standard ways to express magnitude across different designs: Cohen’s d for two-group comparisons and eta squared for variance explained in ANOVA.

The other options don’t directly quantify magnitude in a standardized way. A mean difference is a raw difference that isn’t standardized, p-values tell you about statistical significance under a null hypothesis, and confidence intervals convey precision around an estimate but are not a single measure of effect size themselves.