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Joint Model Evaluation
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Statistics
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Part 1

Using OLS, we regress yy onto X1X_1 and find that the model has an R2R^2 of 0.45. We also regress yy onto X2X_2 and find that the model has an R2R^2 of 0.3. Let [min,max][\min, \max] denote the lower and upper bound of R2R^2 of a model which regresses yy onto X1,X2X_1, X_2. Find both the min\min and max\max R2R^2 values for the new model.