An engineer wants to determine how the weight of a gas powered car, x, affects gas mileage, y. The accompanying days represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. weight Miles per (pounds), x Gallon, y 3797 16 3897 16 2704 24 3608 20 3360 22 3040 22 3787 17 2618 24 3509 18 3798 16 3399 17 Find the least squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. Find the least squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
An engineer wants to determine how the weight of a gas powered car, x, affects gas mileage, y. The accompanying days represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year.
weight Miles per
(pounds), x Gallon, y
3797 16
3897 16
2704 24
3608 20
3360 22
3040 22
3787 17
2618 24
3509 18
3798 16
3399 17
Find the least squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
Find the least squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
y hat = _____x + ______
(Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed).
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
