Question 1

When using best subsets regression, all possible combinations of independent variables are considered when choosing a final model.

Accepted Answer

A) True 
 B)False

Question 2

The ________ measures the total variation in the dependent variable in multiple regression.

Accepted Answer

A) total sum of squares 
B) sum of squares regression 
C) sum of squares error 
D) sum of squares within 
A) total sum of squares 
B) sum of squares regression 
C) sum of squares error 
D) sum of squares within

Question 3

The coefficients for the dummy variables reflect the change in the dependent variable when comparing one category of the qualitative variable to the base category (the one with all zeros).

Accepted Answer

A) True 
 B)False

Question 4

The mean square regression for this model is ______.

Accepted Answer

A) 12,236,421,969 
B) 1,296,648,554 
C) 14,263,134,094 
D) 36,709,265,906 
A) 12,236,421,969 
B) 1,296,648,554 
C) 14,263,134,094 
D) 36,709,265,906

Question 5

The number of employees that were included in the sample is ______.

Accepted Answer

A) 25 
B) 20 
C) 19 
D) 24 
A) 25 
B) 20 
C) 19 
D) 24

Question 6

The multiple coefficient of determination for this model is ______.

Accepted Answer

A) 0.7865 
B) 0.6439 
C) 0.7202 
D) 0.8486 
A) 0.7865 
B) 0.6439 
C) 0.7202 
D) 0.8486

Question 7

Which one of the following statements is true concerning the 95% confidence interval for the regression coefficient for the PEN variable?

Accepted Answer

A) Because the confidence interval includes zero, we have evidence to conclude that there is a relationship between the average number of penalties per game and the average number of wins per season for a team. 
B) Because the confidence interval includes zero, we have evidence to conclude that there is no relationship between the average number of penalties per game and the average number of wins per season for a team. 
C) Because the confidence interval does not include zero, we have evidence to conclude that there is no relationship between the average number of penalties per game and the average number of wins per season for a team. 
D) Because the confidence interval does not include zero, we have evidence to conclude that there is a relationship between the average number of penalties per game and the average number of wins per season for a team. 
A) Because the confidence interval includes zero, we have evidence to conclude that there is a relationship between the average number of penalties per game and the average number of wins per season for a team. 
B) Because the confidence interval includes zero, we have evidence to conclude that there is no relationship between the average number of penalties per game and the average number of wins per season for a team. 
C) Because the confidence interval does not include zero, we have evidence to conclude that there is no relationship between the average number of penalties per game and the average number of wins per season for a team. 
D) Because the confidence interval does not include zero, we have evidence to conclude that there is a relationship between the average number of penalties per game and the average number of wins per season for a team.

Question 8

Which one of the following statements is true?

Accepted Answer

A) The variable FG% has the highest correlation with the number of wins because this variable entered the model first. 
B) The variable TO did not remain in the final model because the regression coefficient is negative. 
C) There is evidence of multicollinearity in this data because only three independent variables were selected for the final model. 
D) The variable REB has the highest correlation with the number of wins because this variable has the lowest p- value in the model. 
A) The variable FG% has the highest correlation with the number of wins because this variable entered the model first. 
B) The variable TO did not remain in the final model because the regression coefficient is negative. 
C) There is evidence of multicollinearity in this data because only three independent variables were selected for the final model. 
D) The variable REB has the highest correlation with the number of wins because this variable has the lowest p- value in the model.

Question 9

In a multiple regression model, a dependent variable explains the variation in the independent variables.

Accepted Answer

A) True 
 B)False

Question 10

The degrees of freedom for the critical value to test the significance of the regression coefficients using α = 0.05 are _______.

Accepted Answer

A) 18 
B) 17 
C) 15 
D) 20 
A) 18 
B) 17 
C) 15 
D) 20

Question 11

Using the multiple regression equation to predict the dependent variable using values of independent variables outside of the range of the original sample can lead to unreliable results.

Accepted Answer

A) True 
 B)False

Question 12

The 95% confidence interval for the regression coefficient for the Bedrooms variable is _____.

Accepted Answer

A) (20,151, 42,373) 
B) (- 8,974, 71,498) 
C) (- 17,502, 80,026) 
D) (7,036, 55,488) 
A) (20,151, 42,373) 
B) (- 8,974, 71,498) 
C) (- 17,502, 80,026) 
D) (7,036, 55,488)

Question 13

If the variance inflation factor exceeds _______, enough correlation exists between the independent variables to claim that multicollinearity is present in the regression model.

Accepted Answer

A) 3.0 
B) 10.0 
C) 6.0 
D) 5.0 
A) 3.0 
B) 10.0 
C) 6.0 
D) 5.0

Question 14

An employee with a bachelor's degree will average ________ more cars sales per month than an employee with an associate's degree.

Accepted Answer

A) 2.5638 
B) 0.4207 
C) 1.3553 
D) 2.9845 
A) 2.5638 
B) 0.4207 
C) 1.3553 
D) 2.9845

Question 15

Every additional turnover differential per season will ________

Accepted Answer

A) increase the average number of wins per season by 1.5572 
B) decrease the average number of wins per season by 1.5572 
C) decrease the average number of wins per season by 0.1371 
D) increase the average number of wins per season by 0.1371 
A) increase the average number of wins per season by 1.5572 
B) decrease the average number of wins per season by 1.5572 
C) decrease the average number of wins per season by 0.1371 
D) increase the average number of wins per season by 0.1371

Question 16

The 95% confidence interval for the regression coefficient for the TO variable is _______.

Accepted Answer

A) (- 0.340, 0.614) 
B) (0.056, 0.218) 
C) (- 0.108, 0.382) 
D) (0.062, 0.212) 
A) (- 0.340, 0.614) 
B) (0.056, 0.218) 
C) (- 0.108, 0.382) 
D) (0.062, 0.212)

Question 17

Every additional bedroom in the house will _______ .

Accepted Answer

A) decrease the average selling price by $101,922 
B) decrease the average selling price by $31,262 
C) increase the average selling price by $31,262 
D) increase the average selling price by $108,597 
A) decrease the average selling price by $101,922 
B) decrease the average selling price by $31,262 
C) increase the average selling price by $31,262 
D) increase the average selling price by $108,597

Question 18

The critical value for the hypothesis test for the overall regression model using α = 0.05 is ______.

Accepted Answer

A) 8.763 
B) 3.708 
C) 3.982 
D) 3.587 
A) 8.763 
B) 3.708 
C) 3.982 
D) 3.587

Question 19

Which one of the following statements is true concerning the 95% confidence interval for the regression coefficient for the Age variable?

Accepted Answer

A) Because the confidence interval does not include zero, we have evidence to conclude that there is no relationship between the age of a house and the selling price of the house. 
B) Because the confidence interval includes zero, we have evidence to conclude that there is no relationship between the age of a house and the selling price of the house. 
C) Because the confidence interval includes zero, we have evidence to conclude that there is a relationship between the age of a house and the selling price of the house. 
D) Because the confidence interval does not include zero, we have evidence to conclude that there is a relationship between the age of a house and the selling price of the house. 
A) Because the confidence interval does not include zero, we have evidence to conclude that there is no relationship between the age of a house and the selling price of the house. 
B) Because the confidence interval includes zero, we have evidence to conclude that there is no relationship between the age of a house and the selling price of the house. 
C) Because the confidence interval includes zero, we have evidence to conclude that there is a relationship between the age of a house and the selling price of the house. 
D) Because the confidence interval does not include zero, we have evidence to conclude that there is a relationship between the age of a house and the selling price of the house.

Question 20

The predicted selling price for a home that is 12 years of age, has 2,500 square feet of living area, and has four bedrooms is ______ .

Accepted Answer

A) $395,240 
B) $443,747 
C) $401,398 
D) $410,366 
A) $395,240 
B) $443,747 
C) $401,398 
D) $410,366

When using best subsets regression, all possible combinations of independent variables are considered when choosing a final model.

The ________ measures the total variation in the dependent variable in multiple regression.

The coefficients for the dummy variables reflect the change in the dependent variable when comparing one category of the qualitative variable to the base category (the one with all zeros).

The mean square regression for this model is ______.

The number of employees that were included in the sample is ______.

The multiple coefficient of determination for this model is ______.

Which one of the following statements is true concerning the 95% confidence interval for the regression coefficient for the PEN variable?

Which one of the following statements is true?

In a multiple regression model, a dependent variable explains the variation in the independent variables.

The degrees of freedom for the critical value to test the significance of the regression coefficients using α = 0.05 are _______.

Using the multiple regression equation to predict the dependent variable using values of independent variables outside of the range of the original sample can lead to unreliable results.

The 95% confidence interval for the regression coefficient for the Bedrooms variable is _____.

If the variance inflation factor exceeds _______, enough correlation exists between the independent variables to claim that multicollinearity is present in the regression model.

An employee with a bachelor's degree will average ________ more cars sales per month than an employee with an associate's degree.

Every additional turnover differential per season will ________

The 95% confidence interval for the regression coefficient for the TO variable is _______.

Every additional bedroom in the house will _______ .

The critical value for the hypothesis test for the overall regression model using α = 0.05 is ______.

Which one of the following statements is true concerning the 95% confidence interval for the regression coefficient for the Age variable?

The predicted selling price for a home that is 12 years of age, has 2,500 square feet of living area, and has four bedrooms is ______ .

Healthy Change

Psychosocial Health

Stress

Relationships and Sexuality

Reproductive Choices

Addiction and Drug Abuse

Alcohol and Tobacco

Nutrition

Weight Management and Body Image

Fitness

Cvd, Cancer, and Diabetes

Infectious Conditions

Violence and Unintentional Injuries

Environmental Health

Forecasting Techniques and Analysis for Time Series Data

Filters

Exam 15: Consumerism and Complementary and Alternative Medicine

When using best subsets regression, all possible combinations of independent variables are considered when choosing a final model.

The ________ measures the total variation in the dependent variable in multiple regression.

The coefficients for the dummy variables reflect the change in the dependent variable when comparing one category of the qualitative variable to the base category (the one with all zeros).

The mean square regression for this model is ______.

The number of employees that were included in the sample is ______.

The multiple coefficient of determination for this model is ______.

Which one of the following statements is true concerning the 95% confidence interval for the regression coefficient for the PEN variable?

Which one of the following statements is true?

In a multiple regression model, a dependent variable explains the variation in the independent variables.

The degrees of freedom for the critical value to test the significance of the regression coefficients using α = 0.05 are _______.

Using the multiple regression equation to predict the dependent variable using values of independent variables outside of the range of the original sample can lead to unreliable results.

The 95% confidence interval for the regression coefficient for the Bedrooms variable is _____.

If the variance inflation factor exceeds _______, enough correlation exists between the independent variables to claim that multicollinearity is present in the regression model.

An employee with a bachelor's degree will average ________ more cars sales per month than an employee with an associate's degree.

Every additional turnover differential per season will ________

The 95% confidence interval for the regression coefficient for the TO variable is _______.

Every additional bedroom in the house will _______ .

The critical value for the hypothesis test for the overall regression model using α = 0.05 is ______.

Which one of the following statements is true concerning the 95% confidence interval for the regression coefficient for the Age variable?

The predicted selling price for a home that is 12 years of age, has 2,500 square feet of living area, and has four bedrooms is ______ .

Healthy Change

Psychosocial Health

Stress

Relationships and Sexuality

Reproductive Choices

Addiction and Drug Abuse

Alcohol and Tobacco

Nutrition

Weight Management and Body Image

Fitness

Cvd, Cancer, and Diabetes

Infectious Conditions

Violence and Unintentional Injuries

Environmental Health

Forecasting Techniques and Analysis for Time Series Data

Filters