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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.
The adjusted R-squared is a modified version of R-squared for the number of predictors in a model. The adjusted R-squared can be negative, but isn't always, while an R-squared value is between zero and 100 and shows the linear relationship in the sample of data even when there is no basic relationship.The adjusted R-squared is the best estimate of the degree of relationship in the basic population.y Investopedia AAA |. A: One major difference between R-squared and the adjusted R-squared is that R-squared supposes that every independent variable in the model explains the variation in the dependent variable.