Question 1

What are the effects of two independent variables that are highly correlated? What can be done to remedy the problem?

Accepted Answer

The high correlation between two variabl

Question 2

The number of observations minus the number of estimated coefficients in a regression equation is called:

Accepted Answer

A) degrees of freedom. 
B) variance. 
C) standard error fo the regression. 
D) none of the above. 
A) degrees of freedom. 
B) variance. 
C) standard error fo the regression. 
D) none of the above.

Question 3

Briefly explain why empirical consumer demand studies such as Patrick McCarthy's study of automobile demand are relevant to managers.

Accepted Answer

Such studies illustrate the types of dat

Question 4

The overall predictive power of the estimated regression equation is measured by the F-statistic.

Accepted Answer

A) True 
 B)False

Question 5

In a multiple regression problem involving two independent variables,if b₁ is computed to be +2.0,it means that:

Accepted Answer

A) the relationship between X₁ and Y is significant. 
B) the estimated value of Y increases by an average of 2 units for each increase of 1 unit of X₁, holding X₂ constant. 
C) the estimated value of Y increases by an average of 2 units for each increase of 1 unit of X₁, without regard to X₂. 
D) the estimated average value of Y is 2 when X₁ equals zero. 
A) the relationship between X₁ and Y is significant. 
B) the estimated value of Y increases by an average of 2 units for each increase of 1 unit of X₁, holding X₂ constant. 
C) the estimated value of Y increases by an average of 2 units for each increase of 1 unit of X₁, without regard to X₂. 
D) the estimated average value of Y is 2 when X₁ equals zero.

Question 6

The range of values in which we can be confident that the true regression coefficient lies within a given degree of probability is called a:

Accepted Answer

A) prediction interval. 
B) confidence interval. 
C) logistic regression. 
D) none of the above. 
A) prediction interval. 
B) confidence interval. 
C) logistic regression. 
D) none of the above.

Question 7

Adjusted R² gives the actual percentage of the variation in the dependent variable explained by the regression model.

Accepted Answer

A) True 
 B)False

Question 8

The intercept of the equation: Y = .09 + 1.5X is 1.5.

Accepted Answer

A) True 
 B)False

Question 9

An estimated regression coefficient is 10 with a standard error of 5.The null hypothesis is that the partial regression coefficient equals one.What is the value of the t-statistic for testing the null hypothesis of the regression coefficient?

Accepted Answer

A) 1 
B) 2 
C) 1.8 
D) 0.5 
A) 1 
B) 2 
C) 1.8 
D) 0.5

Question 10

The least squares regression is based on:

Accepted Answer

A) maximizing the absolute sum of squares errors. 
B) minimizing the absolute sum of squares errors. 
C) maximizing the sum of squared errors. 
D) minimizing the sum of squared errors. 
A) maximizing the absolute sum of squares errors. 
B) minimizing the absolute sum of squares errors. 
C) maximizing the sum of squared errors. 
D) minimizing the sum of squared errors.

Question 11

When using expert opinion,consumer surveys,test marketing,and price experiments to analyze consumer behavior,managers must consider how to isolate the effect of different variables that influence demand.

Accepted Answer

A) True 
 B)False

Question 12

The coefficient of determination represents the ratio of the regression sum of squares to the total sum of squares.

Accepted Answer

A) True 
 B)False

Question 13

The total sum of squares equals the sum of squares of the variation explained by the regression and the sum of squares of the errors.

Accepted Answer

A) True 
 B)False

Question 14

Scenario 2: Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses.
  
-Refer to Scenario 2.What percentage of the variation in the dependent variable,Market Value,is explained by the regression model?

Accepted Answer

The coefficient of determinati

Question 15

Regression analysis that analyzes the relationship between one dependent variable and several independent variables is called:

Accepted Answer

A) simple regression analysis. 
B) correlation analysis. 
C) multiple regression analysis. 
D) cluster analysis. 
A) simple regression analysis. 
B) correlation analysis. 
C) multiple regression analysis. 
D) cluster analysis.

Question 16

Scenario 1: The demand model relating the quantity of good XYZ sold (QXYZ)to the price of good (PXYZ)is reported below:
  
-Refer to Scenario 1.What is the total sum of squares?

Accepted Answer

A) 3860.8 
B) 3718.9 
C) 141.9 
D) None of the above. 
A) 3860.8 
B) 3718.9 
C) 141.9 
D) None of the above.

Question 17

All of the following are limitations of direct consumer surveys except:

Accepted Answer

A) the possibility that consumers' responses may not reflect their actual behavior in the market place. 
B) the possibility of response biases because survey respondents may not want to reveal their true preferences. 
C) the likelihood that respondents will deliberately and systematically mislead interviewers. 
D) the possibility that the type of questions asked may unintentionally bias the respondent's answers. 
A) the possibility that consumers' responses may not reflect their actual behavior in the market place. 
B) the possibility of response biases because survey respondents may not want to reveal their true preferences. 
C) the likelihood that respondents will deliberately and systematically mislead interviewers. 
D) the possibility that the type of questions asked may unintentionally bias the respondent's answers.

Question 18

Scenario 2: Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses.
  
-Refer to Scenario 2.If the age of a house is 25 years with 1,500 square feet,what is the estimated market value of the house?

Accepted Answer

Market Value = 47331

Question 19

The total sum of squares is 400 and the sum of squares errors is 100,what is the coefficient of determination?

Accepted Answer

A) 25 
B) 0.75 
C) 1.00 
D) 0 
A) 25 
B) 0.75 
C) 1.00 
D) 0

Question 20

Scenario 2: Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses.
  
-Refer to Scenario 2.If the age of a house increases by 1 year given that the square feet is held constant,what is the impact on the house's market value?

Accepted Answer

The Market

What are the effects of two independent variables that are highly correlated? What can be done to remedy the problem?

The number of observations minus the number of estimated coefficients in a regression equation is called:

Briefly explain why empirical consumer demand studies such as Patrick McCarthy's study of automobile demand are relevant to managers.

The overall predictive power of the estimated regression equation is measured by the F-statistic.

In a multiple regression problem involving two independent variables,if b₁ is computed to be +2.0,it means that:

The range of values in which we can be confident that the true regression coefficient lies within a given degree of probability is called a:

Adjusted R² gives the actual percentage of the variation in the dependent variable explained by the regression model.

The intercept of the equation: Y = .09 + 1.5X is 1.5.

An estimated regression coefficient is 10 with a standard error of 5.The null hypothesis is that the partial regression coefficient equals one.What is the value of the t-statistic for testing the null hypothesis of the regression coefficient?

The least squares regression is based on:

When using expert opinion,consumer surveys,test marketing,and price experiments to analyze consumer behavior,managers must consider how to isolate the effect of different variables that influence demand.

The coefficient of determination represents the ratio of the regression sum of squares to the total sum of squares.

The total sum of squares equals the sum of squares of the variation explained by the regression and the sum of squares of the errors.

Regression analysis that analyzes the relationship between one dependent variable and several independent variables is called:

Scenario 1: The demand model relating the quantity of good XYZ sold (QXYZ)to the price of good (PXYZ)is reported below: -Refer to Scenario 1.What is the total sum of squares?

All of the following are limitations of direct consumer surveys except:

The total sum of squares is 400 and the sum of squares errors is 100,what is the coefficient of determination?

Managers and Economics

Demand, supply, and Equilibrium Prices

Demand Elasticities

Production and Cost Analysis in the Short Run

Production and Cost Analysis in the Long Run

Market Structure: Perfect Competition

Market Structure: Monopoly and Monopolistic Competition

Market Structure: Oligopoly

Pricing Strategies for the Firm

Measuring Macroeconomic Activity

Spending by Individuals, firms, and Governments on Real Goods and Services

The Role of Money in the Macro Economy

The Aggregate Model of the Macro Economy

International and Balance of Payments Issues in the Macro Economy

Combining Micro and Macro Analysis for Managerial Decision Making

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Exam 4: Techniques for Understanding Consumer Demand and Behavior

What are the effects of two independent variables that are highly correlated? What can be done to remedy the problem?

The number of observations minus the number of estimated coefficients in a regression equation is called:

Briefly explain why empirical consumer demand studies such as Patrick McCarthy's study of automobile demand are relevant to managers.

The overall predictive power of the estimated regression equation is measured by the F-statistic.

In a multiple regression problem involving two independent variables,if b₁ is computed to be +2.0,it means that:

The range of values in which we can be confident that the true regression coefficient lies within a given degree of probability is called a:

Adjusted R² gives the actual percentage of the variation in the dependent variable explained by the regression model.

The intercept of the equation: Y = .09 + 1.5X is 1.5.

An estimated regression coefficient is 10 with a standard error of 5.The null hypothesis is that the partial regression coefficient equals one.What is the value of the t-statistic for testing the null hypothesis of the regression coefficient?

The least squares regression is based on:

When using expert opinion,consumer surveys,test marketing,and price experiments to analyze consumer behavior,managers must consider how to isolate the effect of different variables that influence demand.

The coefficient of determination represents the ratio of the regression sum of squares to the total sum of squares.

The total sum of squares equals the sum of squares of the variation explained by the regression and the sum of squares of the errors.

Regression analysis that analyzes the relationship between one dependent variable and several independent variables is called:

Scenario 1: The demand model relating the quantity of good XYZ sold (QXYZ)to the price of good (PXYZ)is reported below: -Refer to Scenario 1.What is the total sum of squares?

All of the following are limitations of direct consumer surveys except:

The total sum of squares is 400 and the sum of squares errors is 100,what is the coefficient of determination?

Managers and Economics

Demand, supply, and Equilibrium Prices

Demand Elasticities

Production and Cost Analysis in the Short Run

Production and Cost Analysis in the Long Run

Market Structure: Perfect Competition

Market Structure: Monopoly and Monopolistic Competition

Market Structure: Oligopoly

Pricing Strategies for the Firm

Measuring Macroeconomic Activity

Spending by Individuals, firms, and Governments on Real Goods and Services

The Role of Money in the Macro Economy

The Aggregate Model of the Macro Economy

International and Balance of Payments Issues in the Macro Economy

Combining Micro and Macro Analysis for Managerial Decision Making

Filters