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 (PriceHub web site, February 24, 2012). What does the scatter chart indicate about the relationship between price and miles? The scatter chart indicates there may be a linear relationship between miles and price. Since a Camry with higher miles will generally sell for a lower price, a] relationship is expected between these two variables. This scatter chart consistent with what is expected. (b) 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) 9= 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 \# in the data set, which has miles, and sells for $ less than its predicted price. The second best bargain is the Camry \# in the data set, which has miles, and sells for less than its predicted price. (f) Suppose that you are considering purchasing a previously owned Camry that has been driven 80,000 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: s (a) Choose a scatter chart below with 'Miles (1000s)' as the independent variable. (c) Test whether each of the regression parameters 0 and t is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? (i) We can conclude that both 0 and 1 are equal to zero, where 0 is the estimated change in price in thousands of dollars for a increase of 1,000 miles and , is the estimated price in thousands of dollars when the number of miles is zero. The interpretation of 0 is not reasonable but the interpretation of 1 is reasonable. (ii) We cannot conclude that neither 0 nor 1 are equal to zero, where 0 is the estimated price in thousands of dollars when the number of miles is zero and i is the estimated change in price in thousands of dollars for a increase of 1,000 miles. The interpretation of 0 is reasonable but the interpretation of 1 is not reasonable: (iii) We can conclude that neither 0 nor 1 are equal to zero, where 0 is the estimated price in thousands of dollars when the number of miles is zero and , is the estimated change in price in thousands of dollars for a increase of 1,000 miles. The interpretation of 0 is not reasonable but the interpretation of 1 is reasonable. (iv) We can conclude that 0=0 but 1=0, where 0 is the estimated change in price in thousands of dollars for a increase of 1,000 miles and 1 is the estimated price in thousands of dollars when the number of miles is zero. Both interpretations are reasonable. (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. 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 (PriceHub web site, February 24, 2012). What does the scatter chart indicate about the relationship between price and miles? The scatter chart indicates there may be a linear relationship between miles and price. Since a Camry with higher miles will generally sell for a lower price, a] relationship is expected between these two variables. This scatter chart consistent with what is expected. (b) 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) 9= 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 \# in the data set, which has miles, and sells for $ less than its predicted price. The second best bargain is the Camry \# in the data set, which has miles, and sells for less than its predicted price. (f) Suppose that you are considering purchasing a previously owned Camry that has been driven 80,000 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: s (a) Choose a scatter chart below with 'Miles (1000s)' as the independent variable. (c) Test whether each of the regression parameters 0 and t is equal to zero at a 0.01 level of significance. What are the correct interpretations of the estimated regression parameters? Are these interpretations reasonable? (i) We can conclude that both 0 and 1 are equal to zero, where 0 is the estimated change in price in thousands of dollars for a increase of 1,000 miles and , is the estimated price in thousands of dollars when the number of miles is zero. The interpretation of 0 is not reasonable but the interpretation of 1 is reasonable. (ii) We cannot conclude that neither 0 nor 1 are equal to zero, where 0 is the estimated price in thousands of dollars when the number of miles is zero and i is the estimated change in price in thousands of dollars for a increase of 1,000 miles. The interpretation of 0 is reasonable but the interpretation of 1 is not reasonable: (iii) We can conclude that neither 0 nor 1 are equal to zero, where 0 is the estimated price in thousands of dollars when the number of miles is zero and , is the estimated change in price in thousands of dollars for a increase of 1,000 miles. The interpretation of 0 is not reasonable but the interpretation of 1 is reasonable. (iv) We can conclude that 0=0 but 1=0, where 0 is the estimated change in price in thousands of dollars for a increase of 1,000 miles and 1 is the estimated price in thousands of dollars when the number of miles is zero. Both interpretations are reasonable. (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