An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. Click here to view the weight and gas mileage data. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y = [ x + 0 (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) A. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. It is not appropriate to interpret the y-intercept. O B. A weightless car will get miles per gallon, on average. It is not appropriate to interpret the slope. O C. For every pound added to the weight of the car, gas mileage in the city will decrease by mile(s) per gallon, on average. A weightless car will get miles per gallon, on average. O D. It is not appropriate to interpret the slope or the y-intercept. (c) A certain gas-powered car weighs 3700 pounds and gets 19 miles per gallon. Is the miles per gallon of this car above average or below average for cars of this weight? Car Weight and MPG O Above Weight O Below Miles per (pounds), x Gallon, y (d) Would it be reasonable to use the least-squares regression line to predict the miles per gallon of a hybrid gas and electric car? Why or why not? 3812 3859 O A. No, because the absolute value of the correlation coefficient is less than the critical value for a sample size of n = 11. 2807 O B. No, because the hybrid is a different type of car. 3516 3292 O C. Yes, because the hybrid is partially powered by gas. 3037 O D. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample size of n = 11. 3704 2605 3483 3787 3370