The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends on many factors, including the model year, mileage, and condition. To investigate the relationship between the car’s mileage and the sales price for Camrys, the following data show the mileage and sale price for 19 sales
Miles (1,000s) | Price ($1,000s) | ||||
22 | 16.2 | ||||
29 | 16.0 | ||||
36 | 13.8 | ||||
47 | 11.5 | ||||
63 | 12.5 | ||||
77 | 12.9 | ||||
73 | 11.2 | ||||
87 | 13.0 | ||||
92 | 11.8 | ||||
101 | 10.8 | ||||
110 | 8.3 | ||||
28 | 12.5 | ||||
59 | 11.1 | ||||
68 | 15.0 | ||||
68 | 12.2 | ||||
91 | 13.0 | ||||
42 | 15.6 | ||||
65 | 12.7 | ||||
110 | 8.3 |
1. Develop an estimated regression equation showing how price is related to miles. What is the estimated regression model?Let x represent the miles.If required, round your answers to four decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300)= + x
y hat = 16.47 + -0.0588x
2. How much of the variation in the sample values of price does the model estimated in part (1) explain?If required, round your answer to two decimal places.
For the model estimated in part (1), 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.
3. The best bargain is the Camry # 12 in the data set, which has ____ miles, and sells for $_____ less than its predicted price.The second best bargain is the Camry #4 in the data set, which has ____ miles, and sells for $___ less than its predicted price.
(4) Suppose that you are considering purchasing a previously owned Camry that has been driven 40,000 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.
Predicted price: $_____
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