Answer:
Compare the predictions in terms of the predictors that were used, the magnitude of the difference between the two predictions, and the advantages and disadvantages of the two methods.
Our predictions for the two models were very simmilar. A difference of $32.78 (less than 1% of the total price of the car) is statistically insignificant in this case. Our binned model returned a whole number while the full model returned a more “accurate” price, but ultimately it is a wash. Both models had comparable accuracy, but the full regression seemed to be better trained. If we wanted to use the binned model I would suggest creating smaller bin ranges to prevent underfitting the model. However, when considering the the overall accuracy range and the car sale market both models would be
Explanation:
