(d) How much of the variation in the sample values of price does the model estimated in part (b) explain?
If required, round your answer to two decimal places.
53.87%
(e) For the model estimated in part (b), calculate the predicted price and residual for each automobile in the data. Identify the two automobiles that were the biggest bargains.
If required, round your answer to the nearest whole number.
The best bargain is the Camry # 12 in the data set, which has 28000 miles, and sells for $ less than its predicted price.
The second best bargain is the Camry # 4 in the data set, which has 47000 miles, and sells for $ less than its predicted price.
(f) Suppose that you are considering purchasing a previously owned Camry that has been driven 60,000 miles. Use the estimated regression equation developed in part (b) to predict the price for this car.
If required, round your answer to one decimal place. Do not round intermediate calculations. Enter your answer in dollars. For example, 12 thousand should be entered as 12,000.
Predicted price: $
Is this the price you would offer the seller? Explain.
(i) Regardless of other factors not considered in the model (various options, the physical condition of the body and interior, etc.), this is not a reasonable price to expect to pay for a Camry that has been driven 60,000 miles miles.
(ii) Depending on other factors not considered in the model (various options, the physical condition of the body and interior, etc.), this is a reasonable price to expect to pay for a Camry that has been driven 60,000 miles miles.
Option (ii)