Suppose we have a collection of cars, we measure their weights and fuel efficiencies, and generate the
following graph of the data. Note: automobile fuel efficiency is often measured in mpg (miles that the car can
be driven per one gallon of gas).
70
60
50
40
MPG
30
$
20
10
0
0
10
20
50
60
30
40
Weight (100 lbs)
For this data set, X represents the weight of each car in hundreds of pounds, and Y represents the predicted
fuel efficiency of each car in miles per gallon (mpg).
Here's the least squares regression line for this data set is Y = -1.11X + 68.17.
Use the given equation of the regression line to predict the mpg rating of a car that weighs 3700 lbs.
0 27.1 mpg
O 64.063 mpg
O 109.24
O 4175.17 mpg
O-4038.83 mpg

Suppose we have a collection of cars we measure their weights and fuel efficiencies and generate the following graph of the data Note automobile fuel efficiency class=

Respuesta :

Answer:the following graph of the data. Note: automobile fuel efficiency is often measured in mpg (miles that the car can be driven per one gallon of gas)

Step-by-step explanation:

If the weight of the car is 3700 lbs then the MPG rating of the car is 27.1 MPG. Then the correct option is A.

What is the linear system?

A Linear system is a system in which the degree of the variable in the equation is one. It may contain one, two, or more than two variables.

Suppose we have a collection of cars, we measure their weights and fuel efficiencies and generate the following graph of the data.

For this data set, X represents the weight of each car in hundreds of pounds, and Y represents the predicted fuel efficiency of each car in miles per gallon (mpg).

Here are the least-squares regression line for this data set is

Y = -1.11X + 68.17.

If the weight of the car is 3700 lbs then the MPG rating of the car will be

Y = -1.11 × 37 + 68.17.

Y = 27.1

More about the linear system link is given below.

https://brainly.com/question/20379472

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