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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.
R-squared is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination, or the coefficient of multiple determination for multiple regression.The definition of R-squared is fairly straight-forward; it is the percentage of the response variable variation that is explained by a linear model.-squared = Explained variation / Total variation. R-squared is always between 0 and 100%: 1  0% indicates that the model explains none of the variability of the response data around its mean. 2  100% indicates that the model explains all the variability of the response data around its mean.