Question 1

Describe a formal test for heteroscedasticity.Explain why a test with this design is likely to identify heteroscedasticity.

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Question 2

Write the model specification and define the variables for a multiple regression model to predict college GPA as a function of entering SAT scores and the year in college: freshman,sophomore,junior,and senior.

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Question 3

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 estimate your model correcting for this heteroscedasticity?

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Question 4

Suppose a scatter plot of your data between X and Y looks as shown below.How might you model Y?

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Question 5

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 at the 5% level,against the obvious one-sided alternative,the null hypothesis that,all else being equal,advertising does not affect expenditures on clothes in this market.

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Question 6

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?

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Question 7

From the regression results we calculate a Durbin-Watson test statistic of 1.53.What can we conclude about the possibility of autocorrelation in this model at α = 0.05?

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The answer of From the regression results we calculate a...

Question 8

The model y_t = 8 + 2.5x_t+ 0.35y_t_-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period t?

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Question 9

The model y_t = 8 + 2.1x_t+ 0.25y_t_-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period (t + 1)?

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Question 10

What strategies can be employed to detect multicollinearity?

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Question 11

Suppose a scatter plot of your data between X and Y looks as shown below.How might you model Y?

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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
-With advertising held fixed,what would be the expected impact over time of a $1 increase in disposable income per student on clothing expenditure?

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

Question 13

Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem?

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Question 14

Briefly discuss approaches that can be employed in situations where multicollinearity is detected.

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Question 15

The model y_t = 12 + 2.4x_t+ 0.5y_t_-1is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period (t + 2)?

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The answer of The model y_t = 12 + 2.4x_t_...

Question 16

Why is it so important to understand and test the assumptions of the multiple regression model?

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The answer of Why is it so important to understand...

Question 17

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?

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The answer of The model y_t = 10 + 4.5x_t_...

Question 18

Write the model specification and define the variables for a multiple regression model to predict wages in U.S.dollars as a function of years of experience and country of employment,indicated as Austria,France,Germany,Japan,and United States.

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Question 19

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?

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The answer of From the regression results we calculate a...

Question 20

From the regression results we calculate a Durbin-Watson test statistic of 2.68.What can we conclude about the possibility of autocorrelation in this model at α=0.05?

Accepted Answer

The answer of From the regression results we calculate a...

Quiz 13: Additional Topics in Regression Analysis

Describe a formal test for heteroscedasticity.Explain why a test with this design is likely to identify heteroscedasticity.

Write the model specification and define the variables for a multiple regression model to predict college GPA as a function of entering SAT scores and the year in college: freshman,sophomore,junior,and senior.

Suppose a scatter plot of your data between X and Y looks as shown below.How might you model Y?

From the regression results we calculate a Durbin-Watson test statistic of 1.53.What can we conclude about the possibility of autocorrelation in this model at α = 0.05?

The model yt = 8 + 2.5xt + 0.35yt-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period t?

The model yt = 8 + 2.1xt + 0.25yt-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period (t + 1)?

What strategies can be employed to detect multicollinearity?

Suppose a scatter plot of your data between X and Y looks as shown below.How might you model Y?

Three predictor variables are being considered for use in a linear regression model.Given the correlation matrix below,does it appear that multicollinearity could be a problem?

Briefly discuss approaches that can be employed in situations where multicollinearity is detected.

The model yt = 12 + 2.4xt + 0.5yt-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period (t + 2)?

Why is it so important to understand and test the assumptions of the multiple regression model?

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?

Write the model specification and define the variables for a multiple regression model to predict wages in U.S.dollars as a function of years of experience and country of employment,indicated as Austria,France,Germany,Japan,and United States.

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?

From the regression results we calculate a Durbin-Watson test statistic of 2.68.What can we conclude about the possibility of autocorrelation in this model at α=0.05?

The model y_t = 8 + 2.5x_t+ 0.35y_t_-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period t?

The model y_t = 8 + 2.1x_t+ 0.25y_t_-1 is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period (t + 1)?

The model y_t = 12 + 2.4x_t+ 0.5y_t_-1is estimated using regression analysis applied to time-series data.What is the effect of a 1-unit increase in x in period (t + 2)?

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?