A common measure of effect size in analysis of variance (ANOVA), symbolized as , quantifies the proportion of variance in the dependent variable that is explained by an independent variable. Computation involves determining the sum of squares between groups (SSbetween) and the total sum of squares (SStotal). The formula is expressed as: = SSbetween / SStotal. For instance, if SSbetween is calculated to be 50 and SStotal is 150, the resulting value is 0.33, indicating that 33% of the variance in the dependent variable is accounted for by the independent variable.
Understanding the proportion of variance explained offers valuable insight into the practical significance of research findings. Unlike p-values, which are influenced by sample size, this measure provides a standardized index of effect magnitude, facilitating comparisons across studies. It provides a more complete understanding of the impact of manipulations or group differences. Its adoption in behavioral and social sciences has grown, contributing to a shift toward effect size reporting alongside statistical significance testing.
