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The weight of a car (in pounds) can influence the mileage (in mpg) that the car can obtain. A random sample of 18 cars was taken and the weight and mileage were recorded for each. The data are in the table below.

The weight of a car (in pounds) can influence the mileage (in mpg) that the car can obtain. A random sample of 18 cars was taken and the weight and mileage were recorded for each. The data are in the table below.

Algebra & Trigonometry with Analytic Geometry
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 94E
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The weight of a car (in pounds) can influence the mileage (in mpg) that the car can obtain. A random sample of 18 cars was taken and the weight and mileage were recorded for each. The data are in the table below.

X, weight (in pounds) Y, mileage (in mpg)
3500 28
2250 41.1
4500 17
3500 28
3500 32.6
3000 31.4
5500 13.2
4000 23.4
4500 19.5
3500 31.3
4000 23.6
2250 53.3
2250 38.9
3000 31.4
2500 40.9
3000 31.5
3000 32.2
2750 36.3
c) Find the equation of the best-fitting line (the least squares regression equation). Round values to 3 decimal places. Include the restricted domain. equation: ? = restricted domain: + pounds <= x <= * X d) Interpret the slope from part c in the context of this problem. (Pay attention to the units) • Every time we increase Select an answer expect Select an answer average. . When Select an answer is Select an answer pounds to be by to Select an answer by e) Interpret the Y-intercept from part c in the context of this problem. Include units. Does it make sense to interpret the Y-intercept on this problem? Why or why not? Select an answer we expect we can f) Should you use the regression equation to predict the mileage of a randomly selected car that has a weight of 4488 pounds? Select an answer on
Transcribed Image Text:c) Find the equation of the best-fitting line (the least squares regression equation). Round values to 3 decimal places. Include the restricted domain. equation: ? = restricted domain: + pounds <= x <= * X d) Interpret the slope from part c in the context of this problem. (Pay attention to the units) • Every time we increase Select an answer expect Select an answer average. . When Select an answer is Select an answer pounds to be by to Select an answer by e) Interpret the Y-intercept from part c in the context of this problem. Include units. Does it make sense to interpret the Y-intercept on this problem? Why or why not? Select an answer we expect we can f) Should you use the regression equation to predict the mileage of a randomly selected car that has a weight of 4488 pounds? Select an answer on
f) Should you use the regression equation to predict the mileage of a randomly selected car that has a weight of 4488 pounds? Select an answer Should you use the regression equation to predict the mileage of a randomly selected car that has a weight of 7948 pounds? Select an answer Looking at your answers above, predict the mileage for the one above that it made sense to do so. Make sure you use the stored equation and not the rounded equation from part c. Round final answer to 3 decimal places. • The predicted mileage for a randomly selected car that has a weight of g) Compute the residual for the following ordered pair in the data: (4000, 23.4). Make sure you use the stored equation and not the rounded equation from part c. Round final answer to 3 decimal places. The residual for the car with a weight of 4000 pounds is Interpret what this value means in the context of this problem. pounds is • The actual mileage of a randomly selected car with a weight of 4000 pounds is Select an answer what was predicted.
Transcribed Image Text:f) Should you use the regression equation to predict the mileage of a randomly selected car that has a weight of 4488 pounds? Select an answer Should you use the regression equation to predict the mileage of a randomly selected car that has a weight of 7948 pounds? Select an answer Looking at your answers above, predict the mileage for the one above that it made sense to do so. Make sure you use the stored equation and not the rounded equation from part c. Round final answer to 3 decimal places. • The predicted mileage for a randomly selected car that has a weight of g) Compute the residual for the following ordered pair in the data: (4000, 23.4). Make sure you use the stored equation and not the rounded equation from part c. Round final answer to 3 decimal places. The residual for the car with a weight of 4000 pounds is Interpret what this value means in the context of this problem. pounds is • The actual mileage of a randomly selected car with a weight of 4000 pounds is Select an answer what was predicted.
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