I am solving a Multiple Linear Regression problem and judging the model by looking at R-square and Adjusted R-square metrics. In recent iteration which are yielding desired coefficients directionally with respect to Target, I am getting both R-square and Adjusted R-square as 0.73. Can this be possible or is something not right?
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R square value assumes each independent variable (IV) in the model contributes to explaining the variance in the dependent variable.
Adjusted R square, on the other hand, is computed and thus includes only those dependent variables that are statistically significant and actually contribute in the variance explanation of the dependent variable.
You can check the difference in the two values if you build a model with s forward step, adding one IV to the model at a time and increasing the complexity of the model The R- square will increase, but Adjusted R swuare might increase or decrease depending on the statistical significance significance of the newly added IV.
In your case, of you are getting same values for both of them, implies all independent variables are statistically significant in explaining the variance.
