Which effect size is defined as the ratio of the model's sum of squares to the total sum of squares and is often described as the coefficient of determination in a variant?

Which effect size is defined as the ratio of the model's sum of squares to the total sum of squares and is often described as the coefficient of determination in a variant?

• A. Error SSCP (E)
• B. Eta squared (η2)
• C. Exp(B)
• D. F-statistic

Answer: (B)

The key idea here is how much of the total variability in the outcome your model explains. When you take the model’s sum of squares and divide it by the total sum of squares, you get the proportion of total variance accounted for by the model. This measure is eta squared (η²). It serves as the ANOVA analogue to the regression’s R², describing the portion of variance explained by the predictor(s) in a variant of the coefficient of determination. The remaining choices represent related but different concepts: the error sum of squares reflects unexplained variance, Exp(B) is the exponentiated regression coefficient, and the F-statistic tests whether the model provides a better fit than the null model rather than quantifying explained variance. Therefore, the ratio of model to total sum of squares corresponds to eta squared.

The key idea here is how much of the total variability in the outcome your model explains. When you take the model’s sum of squares and divide it by the total sum of squares, you get the proportion of total variance accounted for by the model. This measure is eta squared (η²). It serves as the ANOVA analogue to the regression’s R², describing the portion of variance explained by the predictor(s) in a variant of the coefficient of determination. The remaining choices represent related but different concepts: the error sum of squares reflects unexplained variance, Exp(B) is the exponentiated regression coefficient, and the F-statistic tests whether the model provides a better fit than the null model rather than quantifying explained variance. Therefore, the ratio of model to total sum of squares corresponds to eta squared.