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 (c) 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 i Car Weight and MPG - X (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.) (b) A certain gas-powered car weighs 3500 pounds and gets 21 miles per gallon. Is the miles per gallon of this car above average or below average for cars of this weight? Weight Miles per Gallon, y O Below (pounds), x 3726 17 O Above 3786 15 2772 24 (c) 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? 3527 19 3334 22 O A. No, because the absolute value of the correlation coefficient is less than the critical value for a sample size of n = 11. 2970 24 O B. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample size of n = 11. 3693 16 O C. No, because the hybrid is a different type of car. 2701 23 O D. Yes, because the hybrid is partially powered by gas. 3561 19 3891 18 3230 19