Deck 14: Introduction to Multiple Regression
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Deck 14: Introduction to Multiple Regression
1
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, what is the estimated mean consumption level for an economy with GDP equal to $4 billion and an aggregate price index of 150?
A)$1.39 billion
B)$2.89 billion
C)$4.75 billion
D)$9.45 billion

Referring to Scenario 14-3, what is the estimated mean consumption level for an economy with GDP equal to $4 billion and an aggregate price index of 150?
A)$1.39 billion
B)$2.89 billion
C)$4.75 billion
D)$9.45 billion
$2.89 billion
2
The variation attributable to factors other than the relationship between the independent variables and the explained variable in a regression analysis is represented by
A)regression sum of squares.
B)error sum of squares.
C)total sum of squares.
D)regression mean squares.
A)regression sum of squares.
B)error sum of squares.
C)total sum of squares.
D)regression mean squares.
error sum of squares.
3
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, what is the predicted consumption level for an economy with GDP equal to $4 billion and an aggregate price index of 150?
A)$1.39 billion
B)$2.89 billion
C)$4.75 billion
D)$9.45 billion

Referring to Scenario 14-3, what is the predicted consumption level for an economy with GDP equal to $4 billion and an aggregate price index of 150?
A)$1.39 billion
B)$2.89 billion
C)$4.75 billion
D)$9.45 billion
$2.89 billion
4
SCENARIO 14-2 A professor of industrial relations believes that an individual's wage rate at a factory (Y)depends on his performance rating
and the number of economics courses the employee successfully completed in college
The professor randomly selects 6 workers and collects the following information: 
Referring to Scenario 14-2, for these data, what is the estimated coefficient for performance rating,
A)0.616
B)1.054
C)6.932
D)9.103



Referring to Scenario 14-2, for these data, what is the estimated coefficient for performance rating,

A)0.616
B)1.054
C)6.932
D)9.103
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5
SCENARIO 14-2 A professor of industrial relations believes that an individual's wage rate at a factory (Y)depends on his performance rating
and the number of economics courses the employee successfully completed in college
The professor randomly selects 6 workers and collects the following information: 
Referring to Scenario 14-2, an employee who took 12 economics courses scores 10 on the performance rating.What is her estimated expected wage rate?
A)10.90
B)12.20
C)24.87
D)25.70



Referring to Scenario 14-2, an employee who took 12 economics courses scores 10 on the performance rating.What is her estimated expected wage rate?
A)10.90
B)12.20
C)24.87
D)25.70
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6
In a multiple regression model, which of the following is correct regarding the value of the adjusted
?
A)It can be negative.
B)It has to be positive.
C)It has to be larger than the coefficient of multiple determination.
D)It can be larger than 1.

A)It can be negative.
B)It has to be positive.
C)It has to be larger than the coefficient of multiple determination.
D)It can be larger than 1.
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7
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, the p-value for the regression model as a whole is
A)0.05
B)0.01
C)0.001
D)None of the above.

Referring to Scenario 14-3, the p-value for the regression model as a whole is
A)0.05
B)0.01
C)0.001
D)None of the above.
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8
SCENARIO 14-1 A manager of a product sales group believes the number of sales made by an employee (Y) depends on how many years that employee has been with the company
and how he/she scored on a business aptitude test
A random sample of 8 employees provides the following: 
Referring to Scenario 14-1, if an employee who had been with the company 5 years scored a 9 on the aptitude test, what would his estimated expected sales be?
A)79.09
B)60.88
C)55.62
D)17.98



Referring to Scenario 14-1, if an employee who had been with the company 5 years scored a 9 on the aptitude test, what would his estimated expected sales be?
A)79.09
B)60.88
C)55.62
D)17.98
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9
In a multiple regression problem involving two independent variables, if
is computed to be +2.0, it means that
A)the relationship between
and Y is significant.
B)the estimated mean of Y increases by 2 units for each increase of 1 unit of
holding
constant.
C)the estimated mean of Y increases by 2 units for each increase of 1 unit of
without regard to 
D)the estimated mean of Y is 2 when
equals zero.

A)the relationship between

B)the estimated mean of Y increases by 2 units for each increase of 1 unit of


C)the estimated mean of Y increases by 2 units for each increase of 1 unit of


D)the estimated mean of Y is 2 when

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10
SCENARIO 14-1 A manager of a product sales group believes the number of sales made by an employee (Y) depends on how many years that employee has been with the company
and how he/she scored on a business aptitude test
A random sample of 8 employees provides the following: 
Referring to Scenario 14-1, for these data, what is the value for the regression constant,
A)0.998
B)3.103
C)4.698
D)21.293



Referring to Scenario 14-1, for these data, what is the value for the regression constant,

A)0.998
B)3.103
C)4.698
D)21.293
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11
SCENARIO 14-2 A professor of industrial relations believes that an individual's wage rate at a factory (Y)depends on his performance rating
and the number of economics courses the employee successfully completed in college
The professor randomly selects 6 workers and collects the following information: 
Referring to Scenario 14-2, suppose an employee had never taken an economics course and managed to score a 5 on his performance rating.What is his estimated expected wage rate?
A)10.90
B)12.20
C)17.23
D)25.11



Referring to Scenario 14-2, suppose an employee had never taken an economics course and managed to score a 5 on his performance rating.What is his estimated expected wage rate?
A)10.90
B)12.20
C)17.23
D)25.11
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12
SCENARIO 14-2 A professor of industrial relations believes that an individual's wage rate at a factory (Y)depends on his performance rating
and the number of economics courses the employee successfully completed in college
The professor randomly selects 6 workers and collects the following information: 
Referring to Scenario 14-2, for these data, what is the estimated coefficient for the number of economics courses taken,
A)0.616
B)1.054
C)6.932
D)9.103



Referring to Scenario 14-2, for these data, what is the estimated coefficient for the number of economics courses taken,

A)0.616
B)1.054
C)6.932
D)9.103
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13
In a multiple regression model, the value of the coefficient of multiple determination
A)has to fall between -1 and +1.
B)has to fall between 0 and +1.
C)has to fall between -1 and 0.
D)can fall between any pair of real numbers.
A)has to fall between -1 and +1.
B)has to fall between 0 and +1.
C)has to fall between -1 and 0.
D)can fall between any pair of real numbers.
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14
SCENARIO 14-1 A manager of a product sales group believes the number of sales made by an employee (Y) depends on how many years that employee has been with the company
and how he/she scored on a business aptitude test
A random sample of 8 employees provides the following: 
Referring to Scenario 14-1, for these data, what is the estimated coefficient for the variable representing scores on the aptitude test,
A)0.998
B)3.103
C)4.698
D)21.293



Referring to Scenario 14-1, for these data, what is the estimated coefficient for the variable representing scores on the aptitude test,

A)0.998
B)3.103
C)4.698
D)21.293
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15
SCENARIO 14-1 A manager of a product sales group believes the number of sales made by an employee (Y) depends on how many years that employee has been with the company
and how he/she scored on a business aptitude test
A random sample of 8 employees provides the following: 
Referring to Scenario 14-1, for these data, what is the estimated coefficient for the variable representing years an employee has been with the company,
A)0.998
B)3.103
C)4.698
D)21.293



Referring to Scenario 14-1, for these data, what is the estimated coefficient for the variable representing years an employee has been with the company,

A)0.998
B)3.103
C)4.698
D)21.293
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16
SCENARIO 14-2 A professor of industrial relations believes that an individual's wage rate at a factory (Y)depends on his performance rating
and the number of economics courses the employee successfully completed in college
The professor randomly selects 6 workers and collects the following information: 
Referring to Scenario 14-2, for these data, what is the value for the regression constant,
A)0.616
B)1.054
C)6.932
D)9.103



Referring to Scenario 14-2, for these data, what is the value for the regression constant,

A)0.616
B)1.054
C)6.932
D)9.103
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17
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, the p-value for the aggregated price index is
A)0.05
B)0.01
C)0.001
D)None of the above.

Referring to Scenario 14-3, the p-value for the aggregated price index is
A)0.05
B)0.01
C)0.001
D)None of the above.
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18
The coefficient of multiple determination 
A)measures the variation around the predicted regression equation.
B)measures the proportion of variation in Y that is explained by
C)measures the proportion of variation in Y that is explained by
holding
constant.
D)will have the same sign as

A)measures the variation around the predicted regression equation.
B)measures the proportion of variation in Y that is explained by

C)measures the proportion of variation in Y that is explained by


D)will have the same sign as

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19
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, the p-value for GDP is
A)0.05
B)0.01
C)0.001
D)None of the above.

Referring to Scenario 14-3, the p-value for GDP is
A)0.05
B)0.01
C)0.001
D)None of the above.
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20
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, when the economist used a simple linear regression model with consumption as the dependent variable and GDP as the independent variable, he obtained an
value of 0.971.What additional percentage of the total variation of consumption has been explained by including aggregate prices in the multiple regression?
A)98.2
B)11.1
C)2.8
D)1.1

Referring to Scenario 14-3, when the economist used a simple linear regression model with consumption as the dependent variable and GDP as the independent variable, he obtained an

A)98.2
B)11.1
C)2.8
D)1.1
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21
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, to test whether gross domestic product has a positive impact on consumption, the p-value is
A)0.00005
B)0.0001
C)0.9999
D)0.99995

Referring to Scenario 14-3, to test whether gross domestic product has a positive impact on consumption, the p-value is
A)0.00005
B)0.0001
C)0.9999
D)0.99995
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22
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which the regression model as a whole is significant?
A)0.0005
B)0.001
C)0.01
D)0.05

Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which the regression model as a whole is significant?
A)0.0005
B)0.001
C)0.01
D)0.05
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23
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which each explanatory variable is significant individually?
A)0.001
B)0.010
C)0.025
D)0.050

Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which each explanatory variable is significant individually?
A)0.001
B)0.010
C)0.025
D)0.050
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24
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, when the builder used a simple linear regression model with house size (House)as the dependent variable and family size (Size)as the independent variable, he obtained an r2 value of 1.25%.What additional percentage of the total variation in house size has been explained by including income in the multiple regression?
A)15.00%
B)70.64%
C)71.50%
D)73.62%

Referring to Scenario 14-4, when the builder used a simple linear regression model with house size (House)as the dependent variable and family size (Size)as the independent variable, he obtained an r2 value of 1.25%.What additional percentage of the total variation in house size has been explained by including income in the multiple regression?
A)15.00%
B)70.64%
C)71.50%
D)73.62%
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25
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what annual income (in thousands of dollars)would an individual with a family size of 4 need to attain a predicted 10,000 square foot home (House = 100)?

Referring to Scenario 14-4, what annual income (in thousands of dollars)would an individual with a family size of 4 need to attain a predicted 10,000 square foot home (House = 100)?
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26
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, to test for the significance of the coefficient on gross domestic product, the
value is
A)0.0001
B)0.8330
C)0.8837
D)0.9999

Referring to Scenario 14-3, to test for the significance of the coefficient on gross domestic product, the

A)0.0001
B)0.8330
C)0.8837
D)0.9999
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27
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what fraction of the variability in house size is explained by income and size of family?
A)17.56%
B)70.69%
C)71.89%
D)84.79%

Referring to Scenario 14-4, what fraction of the variability in house size is explained by income and size of family?
A)17.56%
B)70.69%
C)71.89%
D)84.79%
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28
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, one economy in the sample had an aggregate consumption level of $3 billion, a GDP of $3.5 billion, and an aggregate price level of 125.What is the residual for this data point?
A)$2.52 billion
B)$0.48 billion
C)- $1.33 billion
D)- $2.52 billion

Referring to Scenario 14-3, one economy in the sample had an aggregate consumption level of $3 billion, a GDP of $3.5 billion, and an aggregate price level of 125.What is the residual for this data point?
A)$2.52 billion
B)$0.48 billion
C)- $1.33 billion
D)- $2.52 billion
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29
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what annual income (in thousands of dollars)would an individual with a family size of 9 need to attain a predicted 5,000 square foot home (House = 50)?

Referring to Scenario 14-4, what annual income (in thousands of dollars)would an individual with a family size of 9 need to attain a predicted 5,000 square foot home (House = 50)?
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30
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which at least one explanatory variable is significant individually?
A)0.005
B)0.010
C)0.025
D)0.050

Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which at least one explanatory variable is significant individually?
A)0.005
B)0.010
C)0.025
D)0.050
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SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, to test for the significance of the coefficient on aggregate price index, the p-value is
A)0.0001
B)0.8330
C)0.8837
D)0.9999

Referring to Scenario 14-3, to test for the significance of the coefficient on aggregate price index, the p-value is
A)0.0001
B)0.8330
C)0.8837
D)0.9999
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32
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, which of the independent variables in the model are significant at the 5% level?
A)Income only
B)Size only
C)Income and Size
D)None

Referring to Scenario 14-4, which of the independent variables in the model are significant at the 5% level?
A)Income only
B)Size only
C)Income and Size
D)None
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33
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, what is the estimated mean consumption level for an economy with GDP equal to $2 billion and an aggregate price index of 90?
A)$1.39 billion
B)$2.89 billion
C)$4.75 billion
D)$9.45 billion

Referring to Scenario 14-3, what is the estimated mean consumption level for an economy with GDP equal to $2 billion and an aggregate price index of 90?
A)$1.39 billion
B)$2.89 billion
C)$4.75 billion
D)$9.45 billion
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34
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, one individual in the sample had an annual income of $100,000 and a family size of 10.This individual owned a home with an area of 7,000 square feet (House = 70.00).What is the residual (in hundreds of square feet)for this data point?

Referring to Scenario 14-4, one individual in the sample had an annual income of $100,000 and a family size of 10.This individual owned a home with an area of 7,000 square feet (House = 70.00).What is the residual (in hundreds of square feet)for this data point?
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35
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which at most one explanatory variable is significant individually?
A)0.001
B)0.010
C)0.025
D)0.050

Referring to Scenario 14-4, which of the following values for the level of significance is the smallest for which at most one explanatory variable is significant individually?
A)0.001
B)0.010
C)0.025
D)0.050
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36
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, to test whether aggregate price index has a negative impact on consumption, the p-value is _______?
A)0.0001
B)0.4165
C)0.8330
D)0.8837

Referring to Scenario 14-3, to test whether aggregate price index has a negative impact on consumption, the p-value is _______?
A)0.0001
B)0.4165
C)0.8330
D)0.8837
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37
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, one economy in the sample had an aggregate consumption level of $4 billion, a GDP of $6 billion, and an aggregate price level of 200.What is the residual for this data point?
A)$4.39 billion
B)$0.39 billion
C)- $0.39 billion
D)- $1.33 billion

Referring to Scenario 14-3, one economy in the sample had an aggregate consumption level of $4 billion, a GDP of $6 billion, and an aggregate price level of 200.What is the residual for this data point?
A)$4.39 billion
B)$0.39 billion
C)- $0.39 billion
D)- $1.33 billion
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38
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, to test for the significance of the coefficient on aggregate price, the value of the relevant t-statistic is
A)2.365
B)0.143
C)- 0.219
D)- 1.960

Referring to Scenario 14-3, to test for the significance of the coefficient on aggregate price, the value of the relevant t-statistic is
A)2.365
B)0.143
C)- 0.219
D)- 1.960
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39
SCENARIO 14-3 An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below. 
Referring to Scenario 14-3, to test whether aggregate price index has a positive impact on consumption, the p-value is
A)0.0001
B)0.4165
C)0.5835
D)0.8330

Referring to Scenario 14-3, to test whether aggregate price index has a positive impact on consumption, the p-value is
A)0.0001
B)0.4165
C)0.5835
D)0.8330
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40
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what is the predicted house size (in hundreds of square feet)for an individual earning an annual income of $40,000 and having a family size of 4?

Referring to Scenario 14-4, what is the predicted house size (in hundreds of square feet)for an individual earning an annual income of $40,000 and having a family size of 4?
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41
SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what fraction of the variability in sales is explained by spending on capital and wages?
A)27.0%
B)50.9%
C)68.9%
D)83.0%

Referring to Scenario 14-5, what fraction of the variability in sales is explained by spending on capital and wages?
A)27.0%
B)50.9%
C)68.9%
D)83.0%
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42
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, at the 0.01 level of significance, what conclusion should the builder draw regarding the inclusion of Size in the regression model?
A)Size is significant in explaining house size and should be included in the model because its p-value is less than 0.01.
B)Size is significant in explaining house size and should be included in the model because its p-value is more than 0.01.
C)Size is not significant in explaining house size and should not be included in the model because its p-value is less than 0.01.
D)Size is not significant in explaining house size and should not be included in the model because its p-value is more than 0.01.

Referring to Scenario 14-4, at the 0.01 level of significance, what conclusion should the builder draw regarding the inclusion of Size in the regression model?
A)Size is significant in explaining house size and should be included in the model because its p-value is less than 0.01.
B)Size is significant in explaining house size and should be included in the model because its p-value is more than 0.01.
C)Size is not significant in explaining house size and should not be included in the model because its p-value is less than 0.01.
D)Size is not significant in explaining house size and should not be included in the model because its p-value is more than 0.01.
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43
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the value of the partial F test statistic is ____ for H₀ : Variable
does not significantly improve the model after variable
has been included H₁ : Variable
significantly improves the model after variable
has been included

Referring to Scenario 14-4, the value of the partial F test statistic is ____ for H₀ : Variable




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44
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the partial F test for H₀ : Variable
does not significantly improve the model after variable
has been included H₁ : Variable
significantly improves the model after variable
has been included has ____ and ____ degrees of freedom.

Referring to Scenario 14-4, the partial F test for H₀ : Variable




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45
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the coefficient of partial determination
is ____.

Referring to Scenario 14-4, the coefficient of partial determination

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46
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, ____% of the variation in the house size can be explained by the variation in the family income while holding the family size constant.

Referring to Scenario 14-4, ____% of the variation in the house size can be explained by the variation in the family income while holding the family size constant.
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47
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, suppose the builder wants to test whether the coefficient on Size is significantly different from 0.What is the value of the relevant t-statistic?
A)- 0.7630
B)3.2708
C)10.8668
D)60.0864

Referring to Scenario 14-4, suppose the builder wants to test whether the coefficient on Size is significantly different from 0.What is the value of the relevant t-statistic?
A)- 0.7630
B)3.2708
C)10.8668
D)60.0864
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48
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, one individual in the sample had an annual income of $40,000 and a family size of 1.This individual owned a home with an area of 1,000 square feet (House = 10.00).What is the residual (in hundreds of square feet)for this data point?

Referring to Scenario 14-4, one individual in the sample had an annual income of $40,000 and a family size of 1.This individual owned a home with an area of 1,000 square feet (House = 10.00).What is the residual (in hundreds of square feet)for this data point?
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49
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, suppose the builder wants to test whether the coefficient on Income is significantly different from 0.What is the value of the relevant t-statistic?
A)-0.7630
B)3.2708
C)10.8668
D)60.0864

Referring to Scenario 14-4, suppose the builder wants to test whether the coefficient on Income is significantly different from 0.What is the value of the relevant t-statistic?
A)-0.7630
B)3.2708
C)10.8668
D)60.0864
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50
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the partial F test for H₀ : Variable
does not significantly improve the model after variable
has been included H₁ : Variable
significantly improves the model after variable
has been included has ____ and ____ degrees of freedom.

Referring to Scenario 14-4, the partial F test for H₀ : Variable




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51
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the coefficient of partial determination
is ____.

Referring to Scenario 14-4, the coefficient of partial determination

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52
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the observed value of the F-statistic is missing from the printout.What are the degrees of freedom for this F-statistic?
A)2 for the numerator, 47 for the denominator
B)2 for the numerator, 49 for the denominator
C)49 for the numerator, 47 for the denominator
D)47 for the numerator, 49 for the denominator

Referring to Scenario 14-4, the observed value of the F-statistic is missing from the printout.What are the degrees of freedom for this F-statistic?
A)2 for the numerator, 47 for the denominator
B)2 for the numerator, 49 for the denominator
C)49 for the numerator, 47 for the denominator
D)47 for the numerator, 49 for the denominator
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53
SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, which of the independent variables in the model are significant at the 5% level?
A)Capital, Wages
B)Capital
C)Wages
D)None of the above

Referring to Scenario 14-5, which of the independent variables in the model are significant at the 5% level?
A)Capital, Wages
B)Capital
C)Wages
D)None of the above
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54
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test
A)Do not reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on house size.
B)Do not reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on house size.
C)Reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on house size.
D)Reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on house size.

Referring to Scenario 14-4 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test

A)Do not reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on house size.
B)Do not reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on house size.
C)Reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on house size.
D)Reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on house size.
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55
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, the value of the partial F test statistic is ____ for H₀ : Variable
does not significantly improve the model after variable
has been included H₁ : Variable
significantly improves the model after variable
has been included

Referring to Scenario 14-4, the value of the partial F test statistic is ____ for H₀ : Variable




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56
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what is the value of the calculated F test statistic that is missing from the output for testing whether the whole regression model is significant?

Referring to Scenario 14-4, what is the value of the calculated F test statistic that is missing from the output for testing whether the whole regression model is significant?
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57
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, at the 0.01 level of significance, what conclusion should the builder reach regarding the inclusion of Income in the regression model?
A)Income is significant in explaining house size and should be included in the model because its p-value is less than 0.01.
B)Income is significant in explaining house size and should be included in the model because its p-value is more than 0.01.
C)Income is not significant in explaining house size and should not be included in the model because its p-value is less than 0.01.
D)Income is not significant in explaining house size and should not be included in the model because its p-value is more than 0.01.

Referring to Scenario 14-4, at the 0.01 level of significance, what conclusion should the builder reach regarding the inclusion of Income in the regression model?
A)Income is significant in explaining house size and should be included in the model because its p-value is less than 0.01.
B)Income is significant in explaining house size and should be included in the model because its p-value is more than 0.01.
C)Income is not significant in explaining house size and should not be included in the model because its p-value is less than 0.01.
D)Income is not significant in explaining house size and should not be included in the model because its p-value is more than 0.01.
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58
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, ____% of the variation in the house size can be explained by the variation in the family size while holding the family income constant.

Referring to Scenario 14-4, ____% of the variation in the house size can be explained by the variation in the family size while holding the family income constant.
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59
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what are the regression degrees of freedom that are missing from the output?
A)2
B)47
C)49
D)50

Referring to Scenario 14-4, what are the regression degrees of freedom that are missing from the output?
A)2
B)47
C)49
D)50
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60
SCENARIO 14-4 A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below: 
Referring to Scenario 14-4, what are the residual degrees of freedom that are missing from the output?
A)2
B)47
C)49
D)50

Referring to Scenario 14-4, what are the residual degrees of freedom that are missing from the output?
A)2
B)47
C)49
D)50
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61
SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, at the 0.01 level of significance, what conclusion should the microeconomist reach regarding the inclusion of Capital in the regression model?
A)Capital is significant in explaining corporate sales and should be included in the model because its p-value is less than 0.01.
B)Capital is significant in explaining corporate sales and should be included in the model because its p-value is more than 0.01.
C)Capital is not significant in explaining corporate sales and should not be included in the model because its p-value is less than 0.01.
D)Capital is not significant in explaining corporate sales and should not be included in the model because its p-value is more than 0.01.

Referring to Scenario 14-5, at the 0.01 level of significance, what conclusion should the microeconomist reach regarding the inclusion of Capital in the regression model?
A)Capital is significant in explaining corporate sales and should be included in the model because its p-value is less than 0.01.
B)Capital is significant in explaining corporate sales and should be included in the model because its p-value is more than 0.01.
C)Capital is not significant in explaining corporate sales and should not be included in the model because its p-value is less than 0.01.
D)Capital is not significant in explaining corporate sales and should not be included in the model because its p-value is more than 0.01.
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62
SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what is the p-value for Capital?
A)0.01
B)0.025
C)0.05
D)None of the above

Referring to Scenario 14-5, what is the p-value for Capital?
A)0.01
B)0.025
C)0.05
D)None of the above
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SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit
and the amount of insulation in inches
Given below is EXCEL output of the regression model.
![<strong>SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit and the amount of insulation in inches Given below is EXCEL output of the regression model. Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?</strong> A)[256.7522, 639.8328] B)[204.7854, 497.1733] C)[-5.3721, -0.1520] D)[-37.1736, 5.2919]](https://d2lvgg3v3hfg70.cloudfront.net/TB8562/11ebc114_12af_0ab6_8acb_5b4469b7973a_TB8562_00.jpg)
Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?
A)[256.7522, 639.8328]
B)[204.7854, 497.1733]
C)[-5.3721, -0.1520]
D)[-37.1736, 5.2919]
![<strong>SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit and the amount of insulation in inches Given below is EXCEL output of the regression model. Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?</strong> A)[256.7522, 639.8328] B)[204.7854, 497.1733] C)[-5.3721, -0.1520] D)[-37.1736, 5.2919]](https://d2lvgg3v3hfg70.cloudfront.net/TB8562/11ebc114_12af_0ab3_8acb_9738bab43086_TB8562_11.jpg)
![<strong>SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit and the amount of insulation in inches Given below is EXCEL output of the regression model. Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?</strong> A)[256.7522, 639.8328] B)[204.7854, 497.1733] C)[-5.3721, -0.1520] D)[-37.1736, 5.2919]](https://d2lvgg3v3hfg70.cloudfront.net/TB8562/11ebc114_12af_0ab4_8acb_a70dc67cf1d8_TB8562_11.jpg)
![<strong>SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit and the amount of insulation in inches Given below is EXCEL output of the regression model. Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?</strong> A)[256.7522, 639.8328] B)[204.7854, 497.1733] C)[-5.3721, -0.1520] D)[-37.1736, 5.2919]](https://d2lvgg3v3hfg70.cloudfront.net/TB8562/11ebc114_12af_0ab5_8acb_37bf1099ffe4_TB8562_00.jpg)
![<strong>SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit and the amount of insulation in inches Given below is EXCEL output of the regression model. Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?</strong> A)[256.7522, 639.8328] B)[204.7854, 497.1733] C)[-5.3721, -0.1520] D)[-37.1736, 5.2919]](https://d2lvgg3v3hfg70.cloudfront.net/TB8562/11ebc114_12af_0ab6_8acb_5b4469b7973a_TB8562_00.jpg)
Referring to Scenario 14-6, what is the 95% confidence interval for the expected change in heating costs as a result of a 1 degree Fahrenheit change in the daily minimum outside temperature?
A)[256.7522, 639.8328]
B)[204.7854, 497.1733]
C)[-5.3721, -0.1520]
D)[-37.1736, 5.2919]
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SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit
and the amount of insulation in inches
Given below is EXCEL output of the regression model.

Referring to Scenario 14-6 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test
At least one 
A)Do not reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs.
B)Do not reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.
C)Reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs.
D)Reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.




Referring to Scenario 14-6 and allowing for a 1% probability of committing a type I error, what is the decision and conclusion for the test


A)Do not reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs.
B)Do not reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.
C)Reject H₀ and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs.
D)Reject H₀ and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, when the microeconomist used a simple linear regression model with sales as the dependent variable and wages as the independent variable, she obtained an
value of 0.601.What additional percentage of the total variation of sales has been explained by including capital spending in the multiple regression?
A)60.1%
B)31.1%
C)22.9%
D)8.8%

Referring to Scenario 14-5, when the microeconomist used a simple linear regression model with sales as the dependent variable and wages as the independent variable, she obtained an

A)60.1%
B)31.1%
C)22.9%
D)8.8%
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, one company in the sample had sales of $21.439 billion (Sales = 21,439).This company spent $300 million on capital and $700 million on wages. What is the residual (in millions of dollars)for this data point?
A)790.69
B)648.31
C)-648.31
D)-790.69

Referring to Scenario 14-5, one company in the sample had sales of $21.439 billion (Sales = 21,439).This company spent $300 million on capital and $700 million on wages. What is the residual (in millions of dollars)for this data point?
A)790.69
B)648.31
C)-648.31
D)-790.69
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what is the p-value for testing whether Capital has a negative influence on corporate sales?
A)0.05
B)0.2743
C)0.5485
D)0.7258

Referring to Scenario 14-5, what is the p-value for testing whether Capital has a negative influence on corporate sales?
A)0.05
B)0.2743
C)0.5485
D)0.7258
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, suppose the microeconomist wants to test whether the coefficient on Capital is significantly different from 0.What is the value of the relevant t-statistic?
A)0.609
B)2.617
C)4.804
D)25.432

Referring to Scenario 14-5, suppose the microeconomist wants to test whether the coefficient on Capital is significantly different from 0.What is the value of the relevant t-statistic?
A)0.609
B)2.617
C)4.804
D)25.432
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SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit
and the amount of insulation in inches
Given below is EXCEL output of the regression model.

Referring to Scenario 14-6, what is your decision and conclusion for the test
level of significance?
A)Do not reject H₀ and conclude that the amount of insulation has a linear effect on heating costs.
B)Reject H₀ and conclude that the amount of insulation does not have a linear effect on heating costs.
C)Reject H₀ and conclude that the amount of insulation has a linear effect on heating costs.
D)Do not reject H₀ and conclude that the amount of insulation does not have a linear effect on heating costs.




Referring to Scenario 14-6, what is your decision and conclusion for the test

A)Do not reject H₀ and conclude that the amount of insulation has a linear effect on heating costs.
B)Reject H₀ and conclude that the amount of insulation does not have a linear effect on heating costs.
C)Reject H₀ and conclude that the amount of insulation has a linear effect on heating costs.
D)Do not reject H₀ and conclude that the amount of insulation does not have a linear effect on heating costs.
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what are the predicted sales (in millions of dollars)for a company spending $500 million on capital and $200 million on wages?
A)15,800.00
B)16,520.07
C)17,277.49
D)20,455.98

Referring to Scenario 14-5, what are the predicted sales (in millions of dollars)for a company spending $500 million on capital and $200 million on wages?
A)15,800.00
B)16,520.07
C)17,277.49
D)20,455.98
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, one company in the sample had sales of $20 billion (Sales = 20,000).This company spent $300 million on capital and $700 million on wages. What is the residual (in millions of dollars)for this data point?
A)874.55
B)622.87
C)-790.69
D)-983.56

Referring to Scenario 14-5, one company in the sample had sales of $20 billion (Sales = 20,000).This company spent $300 million on capital and $700 million on wages. What is the residual (in millions of dollars)for this data point?
A)874.55
B)622.87
C)-790.69
D)-983.56
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what is the p-value for testing whether Wages have a positive impact on corporate sales?
A)0.01
B)0.05
C)0.0001
D)0.00005

Referring to Scenario 14-5, what is the p-value for testing whether Wages have a positive impact on corporate sales?
A)0.01
B)0.05
C)0.0001
D)0.00005
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what are the predicted sales (in millions of dollars)for a company spending $100 million on capital and $100 million on wages?
A)15,800.00
B)16,520.07
C)17,277.49
D)20,455.98

Referring to Scenario 14-5, what are the predicted sales (in millions of dollars)for a company spending $100 million on capital and $100 million on wages?
A)15,800.00
B)16,520.07
C)17,277.49
D)20,455.98
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, which of the following values for
is the smallest for which the regression model as a whole is significant?
A)0.00005
B)0.001
C)0.01
D)0.05

Referring to Scenario 14-5, which of the following values for

A)0.00005
B)0.001
C)0.01
D)0.05
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, the observed value of the F-statistic is given on the printout as 25.432.What are the degrees of freedom for this F-statistic?
A)25 for the numerator, 2 for the denominator
B)2 for the numerator, 23 for the denominator
C)23 for the numerator, 25 for the denominator
D)2 for the numerator, 25 for the denominator

Referring to Scenario 14-5, the observed value of the F-statistic is given on the printout as 25.432.What are the degrees of freedom for this F-statistic?
A)25 for the numerator, 2 for the denominator
B)2 for the numerator, 23 for the denominator
C)23 for the numerator, 25 for the denominator
D)2 for the numerator, 25 for the denominator
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SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit
and the amount of insulation in inches
Given below is EXCEL output of the regression model.

Referring to Scenario 14-6, what can we say about the regression model?
A)The model explains 17.12% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 27.78% of the sample variability of heating
Costs.
B)The model explains 19.28% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 27.78% of the sample variability of heating
Costs.
C)The model explains 27.78% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 19.28% of the sample variability of heating
Costs.
D)The model explains 19.28% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 17.12% of the sample variability of heating
Costs.




Referring to Scenario 14-6, what can we say about the regression model?
A)The model explains 17.12% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 27.78% of the sample variability of heating
Costs.
B)The model explains 19.28% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 27.78% of the sample variability of heating
Costs.
C)The model explains 27.78% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 19.28% of the sample variability of heating
Costs.
D)The model explains 19.28% of the variability of heating costs; after correcting for the degrees of freedom, the model explains 17.12% of the sample variability of heating
Costs.
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what is the p-value for Wages?
A)0.01
B)0.05
C)0.0001
D)None of the above

Referring to Scenario 14-5, what is the p-value for Wages?
A)0.01
B)0.05
C)0.0001
D)None of the above
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SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit
and the amount of insulation in inches
Given below is EXCEL output of the regression model.

Referring to Scenario 14-6, the estimated value of the regression parameter
in means that
A)holding the effect of the amount of insulation constant, an estimated expected $1 increase in heating costs is associated with a decrease in the daily minimum outside
Temperature by 2.76 degrees.
B)holding the effect of the amount of insulation constant, a 1 degree increase in the daily minimum outside temperature results in a decrease in heating costs by $2.76.
C)holding the effect of the amount of insulation constant, a 1 degree increase in the daily minimum outside temperature results in an estimated decrease in mean heating
Costs by $2.76.
D)holding the effect of the amount of insulation constant, a 1% increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs
By 2.76%.




Referring to Scenario 14-6, the estimated value of the regression parameter

A)holding the effect of the amount of insulation constant, an estimated expected $1 increase in heating costs is associated with a decrease in the daily minimum outside
Temperature by 2.76 degrees.
B)holding the effect of the amount of insulation constant, a 1 degree increase in the daily minimum outside temperature results in a decrease in heating costs by $2.76.
C)holding the effect of the amount of insulation constant, a 1 degree increase in the daily minimum outside temperature results in an estimated decrease in mean heating
Costs by $2.76.
D)holding the effect of the amount of insulation constant, a 1% increase in the daily minimum outside temperature results in an estimated decrease in mean heating costs
By 2.76%.
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what is the p-value for testing whether Capital has a positive influence on corporate sales?
A)0.025
B)0.05
C)0.2743
D)0.5485

Referring to Scenario 14-5, what is the p-value for testing whether Capital has a positive influence on corporate sales?
A)0.025
B)0.05
C)0.2743
D)0.5485
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SCENARIO 14-5 A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression. 
Referring to Scenario 14-5, what is the p-value for testing whether Wages have a negative impact on corporate sales?
A)0.05
B)0.0001
C)0.00005
D)0.99995

Referring to Scenario 14-5, what is the p-value for testing whether Wages have a negative impact on corporate sales?
A)0.05
B)0.0001
C)0.00005
D)0.99995
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