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R², or the coefficient of determination, quantifies the proportion of variance in the dependent variable that is predictable from the independent variables in a regression model, providing a clearer understanding of model fit. In contrast, R (the correlation coefficient) measures the strength and direction of a linear relationship between two variables but does not indicate the explanatory power of a model. Thus, R² offers a more comprehensive evaluation of model performance than R alone.

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