Consider the following data. Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). The following information is based on data taken from Consumer Reports (Vol. 62, No. 4). x 25 44 32 47 23 40 34 52 29 y | 33 22 23 13 17 21 14 A USE SALT Given the least squares line ŷ = 43.8915 - 0.6031x: (a) Make a residual plot for the least-squares model. Be sure to plot the horizontal line at y = 0. y y 1아 1아 5 20 30 40 50 60 20 30 40 50 y y 1아 1아 -5 20 30 40 50 60 20 30 40 50 (b) Use the residual plot to comment about the appropriateness of the least squares model for these data. The residuals do not seem to be scattered randomly around the horizontal line at 0. There do not appear to be any outliers. The residuals do not seem to be scattered randomly around the horizontal line at 0. There do appear to be outliers. The residuals seem to be scattered randomly around the horizontal line at 0. There do not appear to be any outliers. The residuals seem to be scattered randomly around the horizontal line at 0. There do appear to be outliers.

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Consider the following data. Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of
the car (in hundreds of pounds), and let y be the miles per gallon (mpg). The following information is based on data taken from
Consumer Reports (Vol. 62, No. 4).
|x25
34 52
14
44
32
23
47
13
23
40
y| 33
22
29
17
21
A USE SALT
Given the least squares line 9 - 43.8915 - 0.6031x:
(a) Make a residual plot for the least-squares model. Be sure to plot the horizontal line at y = 0.
y
y
1아
1아
-5
20
30
40
50
60
20
30
40 50
y
1아
10f
5
20
30
40
50
60
20
30
40
50
(b) Use the residual plot to comment about the appropriateness of the least squares model for these data.
The residuals do not seem to be scattered randomly around the horizontal line at 0. There do not appear to be any
outliers.
The residuals do not seem to be scattered randomly around the horizontal line at 0. There do appear to be
outliers.
The residuals seem to be scattered randomly around the horizontal line at 0. There do not appear to be any outliers.
The residuals seem to be scattered randomly around the horizontal line at 0. There do appear to be outliers.
Transcribed Image Text:Consider the following data. Do heavier cars really use more gasoline? Suppose a car is chosen at random. Let x be the weight of the car (in hundreds of pounds), and let y be the miles per gallon (mpg). The following information is based on data taken from Consumer Reports (Vol. 62, No. 4). |x25 34 52 14 44 32 23 47 13 23 40 y| 33 22 29 17 21 A USE SALT Given the least squares line 9 - 43.8915 - 0.6031x: (a) Make a residual plot for the least-squares model. Be sure to plot the horizontal line at y = 0. y y 1아 1아 -5 20 30 40 50 60 20 30 40 50 y 1아 10f 5 20 30 40 50 60 20 30 40 50 (b) Use the residual plot to comment about the appropriateness of the least squares model for these data. The residuals do not seem to be scattered randomly around the horizontal line at 0. There do not appear to be any outliers. The residuals do not seem to be scattered randomly around the horizontal line at 0. There do appear to be outliers. The residuals seem to be scattered randomly around the horizontal line at 0. There do not appear to be any outliers. The residuals seem to be scattered randomly around the horizontal line at 0. There do appear to be outliers.
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