Final answer:
Effect size in statistics measures the magnitude of the difference or relationship between variables. Eta squared and partial eta squared are both measures of effect size in ANOVA models. They yield the same value when there is only one factor in the model.
Step-by-step explanation:
Effect Size: Effect size refers to the magnitude of the difference or relationship between variables in statistical analysis. It provides a standardized measure of the strength or impact of the observed effect.
Eta Squared: Eta squared (η²) is a measure of the proportion of variance in the dependent variable that can be explained by the independent variable in an analysis of variance (ANOVA) model. It represents the effect size for the whole model.
Partial Eta Squared: Partial eta squared (η²p) is similar to eta squared, but it represents the effect size for a specific factor or independent variable in an ANOVA model, while controlling for the effects of other factors. It provides a measure of the unique contribution of each factor.
These two types of effect sizes yield the same value when there is only one factor or independent variable in the ANOVA model.