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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.
In a multiple regression, multiple R can be viewed as the correlation between the actual and predicted values of the dependent variable. It can only be between zero and one (since it uses a sum of squares in its calculation, and these cannot be negative).