"he accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= -0.972. The least-squares regress veight as the explanatory variable and miles per gallon as the response variable is y= -0.0070x + 44.4405. Complete parts (a) and (b) below. E Click the icon view the data table. a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon? "he proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is %. Round to one decimal place as needed.) b) Interpret the coefficient of determination. - X % of the variance in Round to one decimal V is V by the linear model. Data Table Full data eot
"he accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= -0.972. The least-squares regress veight as the explanatory variable and miles per gallon as the response variable is y= -0.0070x + 44.4405. Complete parts (a) and (b) below. E Click the icon view the data table. a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon? "he proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is %. Round to one decimal place as needed.) b) Interpret the coefficient of determination. - X % of the variance in Round to one decimal V is V by the linear model. Data Table Full data eot
Chapter4: Linear Functions
Section: Chapter Questions
Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...
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Transcribed Image Text:The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= - 0.972. The least-squares regression line treating
weight as the explanatory variable and miles per gallon as the response variable is y= - 0.0070x + 44.4405. Complete parts (a) and (b) below.
Click the icon to view the data table.
.....
(a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon?
The proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is
%.
(Round to one decimal place as needed.)
(b) Interpret the coefficient of determination.
% of the variance in
is
by the linear model.
Data Table
(Round to one decimal p
Full data set
gas mileage
Miles per
Weight
(pounds), x
Weight
(pounds), x
Miles per
Gallon, y
Car
Car
Gallon, y
weight
Car 1
3,765
18
Car 7
2,605
25
Car 2
3,984
17
Car 8
3,772
17
Car 3
3,530
20
Car 9
3,310
20
Car 4
3,175
22
Car 10
2,991
25
Car 5
2,580
26
Car 11
2,752
26
Car 6
3,730
18
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