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.Weight (pounds), x Miles per Gallon, y3648 163847 172709 253550 183286 202922 233654 172533 253427 183809 173372 19A) Find the​ least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.y with caret = ___x + ___(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.C) A certain? gas-powered car weighs 3600 pounds and gets 20 miles per gallon. Is the miles per gallon of this car above average or below average for cars of this? weight?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?

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Answer:

Step-by-step explanation:

Given the following data :

(Weight, miles per gallon) (x, y) = 3648, 19), (1638, 47), (1727, 09), (2535, 50), (1832, 86), (2029, 22), (2336, 54), (1725, 33), (2534, 27), (1838, 09), (1733, 72)

Using the least square regression calculator  :

y = -0.00941x + 59.07

B) slope = -0.00941

The slope 'm' of the graphical relationship is -0.009406

Intercept = 59.07 ( where the regression line crosses the x-axis)

C.) Using the regression equation:

y = -0.00941(3600) + 59.07

y = 25.194 gallons (above)

D.) No, because other factors also contribute to gas mileage such as cylinders, Displacement, mdoel e. T. C

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