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The value of R square would not decrease when more variables are added to the model. As a result, there is always a temptation to add more variables in the model, because of which problem can arise therefore in that case Adjusted R2 is used as a measure.
â¢ The square of the correlation coefficient, r^2 = the % of the TOTAL variance in the Y scores that be explained by X scores. --> it indicates the accuracy of prediction based on X. --> aka if we know variance of X, we can find out the variance of Y, which is why r is squared (ex.