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I think you inversed the relationship. Multiple R is the correlation between actual and predicted values of the dependant variable. R2 is the modelâs accuracy in explaining the dependant variable. I think there is a testable difference.
R-squared is the proportion of the total sum of squares explained by the model. Rsquared, a property of the fitted model, is a structure with two fields: Ordinary â Ordinary (unadjusted) R-squared. Adjusted â R-squared adjusted for the number of coefficients.