Question 1

Model specification includes selection of the dependent and independent variables and the algebraic form of the model.

Accepted Answer

A) True 
 B)False

Question 2

Consider the regression model   = 10 + 6x1 + 2x2.A 1-unit increase in x2,while holding x1 constant,increases the value of y,on average,by:

Accepted Answer

A) 2 
B) 8 
C) 18 
D) an amount that depends on the value of x1 
A) 2 
B) 8 
C) 18 
D) an amount that depends on the value of x1

Question 3

In many time-series applications,the dependent variable in a time period is often related to the value taken by this variable in the previous time period.

Accepted Answer

A) True 
 B)False

Question 4

Heteroscedasticity is more likely to arise in the log linear regression model.

Accepted Answer

A) True 
 B)False

Question 5

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
Consider the following data for two variables,x and y.The independent variable x represents the amount of training time (in hours)for a salesperson starting a new car dealership to adjust fully,and the dependent variable y represents the weekly sales (in $1000s).
  
-Find the coefficient of determination of this simple linear model.What does this statistic tell you about the model?

Accepted Answer

Since the coefficient of determination R

Question 6

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
Suppose that a regression was run with three independent variables and 30 observations.The Durbin-Watson statistic was 0.64.
-Why is it important to consider all the independent variables together in one model,rather than in separate simple linear regression models?

Accepted Answer

If an important explanatory variable is

Question 7

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
A regression analysis involving 25 observations and four independent variables revealed that the total variation in the dependent variable y is 1600 and that the mean square for error is 20.
-Develop the ANOVA table.

Accepted Answer

The answer of THE NEXT QUESTIONS ARE BASED ON THE...

Question 8

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
Consider the following model: Y = βS1U1B10S1U1B0 + βS1U1B11S1U1B0XS1U1B11S1U1B0S1U1B1tS1U1B0 + βS1U1B12S1U1B0XS1U1B12S1U1B0S1U1B1tS1U1B0 + γS1U1B13S1U1B0YS1U1B1tS1U1B0S1U1B1-1S1U1B0.Using a sample of 36 months,we estimate this model and obtain the following results: yS1U1B1tS1U1B0 = 1.33 + 17.6xS1U1B11S1U1B0S1U1B1tS1U1B0 + 0.94xS1U1B12S1U1B0S1U1B1tS1U1B0S1U1B1 S1U1B0+ 0.39YS1U1B1tS1U1B0S1U1B1-1S1U1B0
-What value would we typically expect for γ3?

Accepted Answer

A) 0  1 
D) γ > 0 
A) 0  1 
D) γ > 0

Question 9

For a sample of 500 college professors,the estimated regression equation is given by   = 275 - 3x - 2D,where y is the retirement age,x is pre-retirement annual income (in $1,000s),and D is a dummy variable that takes the value of 0 for male professors and 1 for female professors.Assume that there is a relationship between y,x,and D.For male professors with pre-retirement income of $70,000,the average age of retirement is:

Accepted Answer

A) 75 
B) 70 
C) 65 
D) 60 
A) 75 
B) 70 
C) 65 
D) 60

Question 10

When models exhibit heteroscedasticity,least squares is the most efficient procedure for estimating the coefficients of the regression model.

Accepted Answer

A) True 
 B)False

Question 11

From the regression results we calculate a Durbin-Watson test statistic of 3.05.What can we conclude about the possibility of autocorrelation in this model at α = 0.05?

Accepted Answer

The decision rule for this test is:
Reje

Question 12

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
A market researcher is interested in the average amount of money spent per year by college students on clothing.From 25 years of annual data,the following estimated regression was obtained through least squares:
yS1U1B1tS1U1B0 = 48.75 +   
+   
+   
where the numbers in parentheses below the coefficients are the coefficient standard errors,and
y = Expenditure per student,in dollars,on clothes
xS1U1B11S1U1B0 = Disposable income per student,in dollars,after the payment of tuition,fees,and room and board.
xS1U1B12S1U1B0 = Index of advertising,aimed at the student market,on clothes
-Test the hypotheses H0 : There is no autocorrelation vs.H1 : There is autocorrelation,given that: Durbin-Watson Statistic d = 1.89,n = 28,k = 3,and α = 0.01

Accepted Answer

Based on the data provided: d_L = 0.97 and

Question 13

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
Suppose we estimate the regression YS1U1B1tS1U1B0 = βS1U1B10S1U1B0 + βS1U1B11S1U1B0xS1U1B11S1U1B0S1U1B1tS1U1B0 + βS1U1B12S1U1B0xS1U1B12S1U1B0S1U1B1tS1U1B0 + βS1U1B13S1U1B0xS1U1B13S1U1B0S1U1B1tS1U1B0 + βS1U1B14S1U1B0xS1U1B14S1U1B0S1U1B1tS1U1B0 + εS1U1B1t S1U1B0using 36 months of data.
-From the regression results we calculate a Durbin-Watson test statistic of 1.03.What can we conclude about the possibility of autocorrelation in this model at α = 0.05?

Accepted Answer

The decision rule for this test is:
Reje

Question 14

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
In a regression based on 35 annual observations,U.S.farm income was related to four independent variables- grain exports,federal government subsidies,population,and a dummy variable for bad weather years.The model was fitted by least squares,resulting in a Durbin-Watson statistic of 1.34.The regression of   
on   
S1U1B1iS1U1B0 yielded a coefficient of determination of 0.036.
-Test the model for heteroscedasticity.

Accepted Answer

n = 35,R² = 0.036 The test stat

Question 15

In regression models,multicollinearity arises when the:

Accepted Answer

A) dependent variables are highly correlated with one another. 
B) independent variables are highly correlated with one another. 
C) independent variables are highly correlated with the dependent variable. 
D) error terms do not have the same variance. 
A) dependent variables are highly correlated with one another. 
B) independent variables are highly correlated with one another. 
C) independent variables are highly correlated with the dependent variable. 
D) error terms do not have the same variance.

Question 16

You are interested in modeling the after-tax profits for your firm over the past 36 months.Which of the following problems would most likely affect your model?

Accepted Answer

A) autocorrelation 
B) multicollinearity 
C) specification bias 
D) heteroscedasticity 
A) autocorrelation 
B) multicollinearity 
C) specification bias 
D) heteroscedasticity

Question 17

Suppose after running the regression Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 and examining a plot of the residuals,you have reason to suspect that there is heteroscedasticity in your model.Assume that the heteroscedasticity is directly proportional to the square of the expected value of the dependent variable.How might you transform your dependent variable to correct for this heteroscedasticity?

Accepted Answer

A) Yi /   
i 
B) Yi - Yi-1 
C) Yi - ρYi-1 
D) (Yi - ρYi-1)/   
i 
A) Yi /   
i 
B) Yi - Yi-1 
C) Yi - ρYi-1 
D) (Yi - ρYi-1)/   
i

Question 18

In a regression model with two predictors x1 and x2,an interaction term may be used when:

Accepted Answer

A) the effect of x1 on the dependent variable is influenced by x2. 
B) both the variables are independent variables. 
C) both variables are influential to each other. 
D) the effect of x2 on the dependent variable is not influenced by x1. 
A) the effect of x1 on the dependent variable is influenced by x2. 
B) both the variables are independent variables. 
C) both variables are influential to each other. 
D) the effect of x2 on the dependent variable is not influenced by x1.

Question 19

The model yt = 10 + 4.5xt + 0.20yt-1 is estimated using regression analysis applied to time-series data.What is the total expected increase over all current and future time periods?

Accepted Answer

Total expected incre

Question 20

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
You are interested in examining the factors that determine the average length of stay in a hospital across states.You collect data on the following variables:
Y = statewide average hospital stay
XS1U1B11S1U1B0 = median state income
XS1U1B12S1U1B0 = 1 if the state is in the Northeast,0 otherwise
XS1U1B13S1U1B0 = 1 if the state is in the South,0 otherwise
XS1U1B14S1U1B0 = 1 if the state is in the Midwest,0 otherwise
XS1U1B15S1U1B0 = 1 if the state is in the West,0 otherwise
-Which of the following model specifications would work for the data provided above?

Accepted Answer

A) Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 
B) Y = β0 + β1X1 + β2X2 + β3X3 + β5X5 
C) Y = β1X1 + β2X2 + β3X3 + β5X5 
D) Y =   
A) Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5X5 
B) Y = β0 + β1X1 + β2X2 + β3X3 + β5X5 
C) Y = β1X1 + β2X2 + β3X3 + β5X5 
D) Y =

Model specification includes selection of the dependent and independent variables and the algebraic form of the model.

Consider the regression model = 10 + 6x₁ + 2x₂.A 1-unit increase in x₂,while holding x₁ constant,increases the value of y,on average,by:

In many time-series applications,the dependent variable in a time period is often related to the value taken by this variable in the previous time period.

Heteroscedasticity is more likely to arise in the log linear regression model.

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: A regression analysis involving 25 observations and four independent variables revealed that the total variation in the dependent variable y is 1600 and that the mean square for error is 20. -Develop the ANOVA table.

When models exhibit heteroscedasticity,least squares is the most efficient procedure for estimating the coefficients of the regression model.

From the regression results we calculate a Durbin-Watson test statistic of 3.05.What can we conclude about the possibility of autocorrelation in this model at α = 0.05?

In regression models,multicollinearity arises when the:

You are interested in modeling the after-tax profits for your firm over the past 36 months.Which of the following problems would most likely affect your model?

In a regression model with two predictors x₁ and x₂,an interaction term may be used when:

The model y_t = 10 + 4.5x_t+ 0.20y_t_-1is estimated using regression analysis applied to time-series data.What is the total expected increase over all current and future time periods?

Describing Data: Graphical

Describing Data: Numerical

Probability

Discrete Random Variables and Probability Distributions

Continuous Random Variables and Probability Distributions

Sampling and Sampling Distributions

Estimation: Single Population

Estimation: Additional Topics

Hypothesis Testing: Single Population

Hypothesis Testing: Additional Topics

Simple Regression

Multiple Regression

Analysis of Categorical Data

Analysis of Variance

Time-Series Analysis and Forecasting

Additional Topics in Sampling

Filters

Exam 13: Additional Topics in Regression Analysis

Model specification includes selection of the dependent and independent variables and the algebraic form of the model.

Consider the regression model = 10 + 6x1 + 2x2.A 1-unit increase in x2,while holding x1 constant,increases the value of y,on average,by:

In many time-series applications,the dependent variable in a time period is often related to the value taken by this variable in the previous time period.

Heteroscedasticity is more likely to arise in the log linear regression model.

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: A regression analysis involving 25 observations and four independent variables revealed that the total variation in the dependent variable y is 1600 and that the mean square for error is 20. -Develop the ANOVA table.

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: Consider the following model: Y = β0 + β1X1t + β2X2t + γ3Yt-1.Using a sample of 36 months,we estimate this model and obtain the following results: yt = 1.33 + 17.6x1t + 0.94x2t + 0.39Yt-1 -What value would we typically expect for γ3?

When models exhibit heteroscedasticity,least squares is the most efficient procedure for estimating the coefficients of the regression model.

From the regression results we calculate a Durbin-Watson test statistic of 3.05.What can we conclude about the possibility of autocorrelation in this model at α = 0.05?

In regression models,multicollinearity arises when the:

You are interested in modeling the after-tax profits for your firm over the past 36 months.Which of the following problems would most likely affect your model?

In a regression model with two predictors x1 and x2,an interaction term may be used when:

The model yt = 10 + 4.5xt + 0.20yt-1 is estimated using regression analysis applied to time-series data.What is the total expected increase over all current and future time periods?

Describing Data: Graphical

Describing Data: Numerical

Probability

Discrete Random Variables and Probability Distributions

Continuous Random Variables and Probability Distributions

Sampling and Sampling Distributions

Estimation: Single Population

Estimation: Additional Topics

Hypothesis Testing: Single Population

Hypothesis Testing: Additional Topics

Simple Regression

Multiple Regression

Analysis of Categorical Data

Analysis of Variance

Time-Series Analysis and Forecasting

Additional Topics in Sampling

Filters

Consider the regression model = 10 + 6x₁ + 2x₂.A 1-unit increase in x₂,while holding x₁ constant,increases the value of y,on average,by:

In a regression model with two predictors x₁ and x₂,an interaction term may be used when:

The model y_t = 10 + 4.5x_t+ 0.20y_t_-1is estimated using regression analysis applied to time-series data.What is the total expected increase over all current and future time periods?