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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.
The previous two examples have suggested how we should define the measure formally. In short, the coefficient of determination or r-squared value, denoted r 2, is the regression sum of squares divided by the total sum of squares. Alternatively, as demonstrated in this, since SSTO = SSR + SSE, the quantity r 2 also equals one minus the ratio of the error sum of squares to the total sum of squares: