An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car A B с 2615 3015 3305 D E Q 3650 31.8 25.8 27.4 21.9 19.4 Weight (pounds), x Miles per Gallon, y 4250 C (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. Write the equation for the least-squares regression line. ý = Ex+D (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.)

MATLAB: An Introduction with Applications
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(a)

An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon.
Car
A B с
2615 3015 3305
D
E Q
4250
3650
31.8 25.8 27.4 21.9 19.4
Weight (pounds), x
Miles per Gallon, y
C
(a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
Write the equation for the least-squares regression line.
ý = x +D
(Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.)
Transcribed Image Text:An engineer wants to determine how the weight of a car, x, affects gas mileage, y. The following data represent the weights of various cars and their miles per gallon. Car A B с 2615 3015 3305 D E Q 4250 3650 31.8 25.8 27.4 21.9 19.4 Weight (pounds), x Miles per Gallon, y C (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. Write the equation for the least-squares regression line. ý = x +D (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.)
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