Question 1

Nonnormal residuals lead to biased estimates of the coefficients in a regression model.

Accepted Answer

A) True 
 B)False

Question 2

Which of the following is not true of the standard error of the regression?

Accepted Answer

A)   It is a measure of the accuracy of the prediction.
B)   It is based on squared vertical deviations between the actual and predicted values of Y.
C)   It would be negative when there is an inverse relationship in the model.
D)   It is used in constructing confidence and prediction intervals for Y.E) A) and B)
F) B) and C)

Question 3

In a multiple regression,which is an incorrect statement about the residuals?

Accepted Answer

A)   They may be used to test for multicollinearity.
B)   They are differences between observed and estimated values of Y.
C)   Their sum will always equal zero.
D)   They may be used to detect heteroscedasticity.E) All of the above
F) A) and D)

Question 4

In a regression model of student grades,we would code the nine categories of business courses taken (ACC,FIN,ECN,MGT,MKT,MIS,ORG,POM,QMM)by including nine binary (0 or 1)predictors in the regression.

Accepted Answer

A) True 
 B)False

Question 5

Refer to this ANOVA table from a regression:  Which statement is not accurate?

Accepted Answer

A)   The F-test is significant at α = .05.
B)   There were 50 observations.
C)   There were 5 predictors.
D)   There would be 50 residuals.E) C) and D)
F) A) and B)

Question 6

Which statement is incorrect?

Accepted Answer

A)   Positive autocorrelation results in too many centerline crossings in the residual plot over time.
B)   The R2 statistic can only increase (or stay the same) when you add more predictors to a regression.
C)   If the F-statistic is insignificant,the t-statistics for the predictors also are insignificant at the same α.
D)   A regression with 60 observations and 5 predictors does not violate Evans' Rule.E) A) and D)
F) A) and C)

Question 7

Autocorrelation of the residuals may affect the reliability of the t values for the estimated coefficients of the predictors X1,X2,... ,Xk.

Accepted Answer

A) True 
 B)False

Question 8

A large VIF (e.g. ,10 or more)would indicate multicollinearity.

Accepted Answer

A) True 
 B)False

Question 9

The ill effects of heteroscedasticity might be mitigated by redefining totals (e.g. ,total number of homicides)as relative values (e.g. ,homicide rate per 100,000 population).

Accepted Answer

A) True 
 B)False

Question 10

A Realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a fireplace (FP is 0 if there is no fireplace,1 if there is a fireplace) .Part of the regression output is provided below,based on a sample of 20 homes.Some of the information has been omitted.  The estimated coefficient for Size is approximately:

Accepted Answer

A)   9.5.
B)   13.8.
C)   122.5.
D)   1442.6.E) B) and C)
F) C) and D)

Question 11

Nonnormality of residuals is not usually considered a major problem unless there are outliers.

Accepted Answer

A) True 
 B)False

Question 12

Which is a characteristic of the variance inflation factor (VIF) ?

Accepted Answer

A)   It is insignificant unless the corresponding t-statistic is significant.
B)   It reveals collinearity rather than multicollinearity.
C)   It measures the degree of significance of each predictor.
D)   It indicates the predictor's degree of multicollinearity.E) A) and B)
F) A) and C)

Question 13

A Realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a fireplace (FP is 0 if there is no fireplace,1 if there is a fireplace) .Part of the regression output is provided below,based on a sample of 20 homes.Some of the information has been omitted.  Which statement is supported by the regression output?

Accepted Answer

A)   At α = .05,FP is not a significant predictor in a two-tailed test.
B)   A fireplace adds around $6476 to the selling price of the average house.
C)   A large house with no fireplace will sell for more than a small house with a fireplace.
D)   FP is a more significant predictor than Size.E) B) and D)
F) All of the above

Question 14

R2adj can exceed R2 if there are several weak predictors.

Accepted Answer

A) True 
 B)False

Question 15

Confidence intervals for Y may be unreliable when the residuals are not normally distributed.

Accepted Answer

A) True 
 B)False

Question 16

The model Y = β0 + β1X + β2X2 cannot be estimated by Excel because of the nonlinear term.

Accepted Answer

A) True 
 B)False

Question 17

A regression of Y using four independent variables X1,X2,X3,X4 could also have up to four nonlinear terms (X2)and six simple interaction terms (XjXk)if you have enough observations to justify them.

Accepted Answer

A) True 
 B)False

Question 18

When autocorrelation is present,the estimates of the coefficients will be unbiased.

Accepted Answer

A) True 
 B)False

Question 19

The relationship of Y to four other variables was established as Y = 12 + 3X1 - 5X2 + 7X3 + 2X4.When X1 increases 5 units and X2 increases 3 units,while X3 and X4 remain unchanged,what change would you expect in your estimate of Y?

Accepted Answer

A)   Decrease by 15
B)   Increase by 15
C)   No change
D)   Increase by 5E) A) and C)
F) None of the above

Question 20

A widening pattern of residuals as X increases would suggest heteroscedasticity.

Accepted Answer

A) True 
 B)False

Exam 13: Multiple Regression

Correct Answer
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Correct Answer
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A widening pattern of residuals as X increases would suggest heteroscedasticity.

Correct Answer
verified

Which is a characteristic of the variance inflation factor (VIF) ?

Correct Answer
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Confidence intervals for Y may be unreliable when the residuals are not normally distributed.

Correct Answer
verified

R²_adj can exceed R² if there are several weak predictors.

Correct Answer
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The ill effects of heteroscedasticity might be mitigated by redefining totals (e.g. ,total number of homicides)as relative values (e.g. ,homicide rate per 100,000 population).

Correct Answer
verified

In a regression model of student grades,we would code the nine categories of business courses taken (ACC,FIN,ECN,MGT,MKT,MIS,ORG,POM,QMM)by including nine binary (0 or 1)predictors in the regression.

Correct Answer
verified

Nonnormal residuals lead to biased estimates of the coefficients in a regression model.

Correct Answer
verified

Nonnormality of residuals is not usually considered a major problem unless there are outliers.

Correct Answer
verified

Which of the following is not true of the standard error of the regression?

Correct Answer
verified

When autocorrelation is present,the estimates of the coefficients will be unbiased.

Correct Answer
verified

In a multiple regression,which is an incorrect statement about the residuals?

Correct Answer
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The relationship of Y to four other variables was established as Y = 12 + 3X₁ - 5X₂ + 7X₃ + 2X₄.When X₁ increases 5 units and X₂ increases 3 units,while X₃ and X₄ remain unchanged,what change would you expect in your estimate of Y?

Correct Answer
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Which statement is incorrect?

Correct Answer
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A large VIF (e.g. ,10 or more)would indicate multicollinearity.

Correct Answer
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A regression of Y using four independent variables X₁,X₂,X₃,X₄ could also have up to four nonlinear terms (X²)and six simple interaction terms (X_jX_k)if you have enough observations to justify them.

Correct Answer
verified

Autocorrelation of the residuals may affect the reliability of the t values for the estimated coefficients of the predictors X₁,X₂,... ,X_k.

Correct Answer
verified

The model Y = β₀ + β₁X + β₂X² cannot be estimated by Excel because of the nonlinear term.

Correct Answer
verified

Refer to this ANOVA table from a regression: Which statement is not accurate?

Correct Answer
verified

Exam 13: Multiple Regression

Correct AnswerverifiedShow Answer

Correct AnswerverifiedShow Answer

A widening pattern of residuals as X increases would suggest heteroscedasticity.

Correct AnswerverifiedShow Answer

Which is a characteristic of the variance inflation factor (VIF) ?

Correct AnswerverifiedShow Answer

Confidence intervals for Y may be unreliable when the residuals are not normally distributed.

Correct AnswerverifiedShow Answer

R2adj can exceed R2 if there are several weak predictors.

Correct AnswerverifiedShow Answer

The ill effects of heteroscedasticity might be mitigated by redefining totals (e.g. ,total number of homicides)as relative values (e.g. ,homicide rate per 100,000 population).

Correct AnswerverifiedShow Answer

In a regression model of student grades,we would code the nine categories of business courses taken (ACC,FIN,ECN,MGT,MKT,MIS,ORG,POM,QMM)by including nine binary (0 or 1)predictors in the regression.

Correct AnswerverifiedShow Answer

Nonnormal residuals lead to biased estimates of the coefficients in a regression model.

Correct AnswerverifiedShow Answer

Nonnormality of residuals is not usually considered a major problem unless there are outliers.

Correct AnswerverifiedShow Answer

Which of the following is not true of the standard error of the regression?

Correct AnswerverifiedShow Answer

When autocorrelation is present,the estimates of the coefficients will be unbiased.

Correct AnswerverifiedShow Answer

In a multiple regression,which is an incorrect statement about the residuals?

Correct AnswerverifiedShow Answer

The relationship of Y to four other variables was established as Y = 12 + 3X1 - 5X2 + 7X3 + 2X4.When X1 increases 5 units and X2 increases 3 units,while X3 and X4 remain unchanged,what change would you expect in your estimate of Y?

Correct AnswerverifiedShow Answer

Which statement is incorrect?

Correct AnswerverifiedShow Answer

A large VIF (e.g. ,10 or more)would indicate multicollinearity.

Correct AnswerverifiedShow Answer

A regression of Y using four independent variables X1,X2,X3,X4 could also have up to four nonlinear terms (X2)and six simple interaction terms (XjXk)if you have enough observations to justify them.

Correct AnswerverifiedShow Answer

Autocorrelation of the residuals may affect the reliability of the t values for the estimated coefficients of the predictors X1,X2,... ,Xk.

Correct AnswerverifiedShow Answer

The model Y = β0 + β1X + β2X2 cannot be estimated by Excel because of the nonlinear term.

Correct AnswerverifiedShow Answer

Refer to this ANOVA table from a regression: Which statement is not accurate?

Correct AnswerverifiedShow Answer

Correct Answer
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Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

R²_adj can exceed R² if there are several weak predictors.

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

The relationship of Y to four other variables was established as Y = 12 + 3X₁ - 5X₂ + 7X₃ + 2X₄.When X₁ increases 5 units and X₂ increases 3 units,while X₃ and X₄ remain unchanged,what change would you expect in your estimate of Y?

Correct Answer
verified

Correct Answer
verified

Correct Answer
verified

A regression of Y using four independent variables X₁,X₂,X₃,X₄ could also have up to four nonlinear terms (X²)and six simple interaction terms (X_jX_k)if you have enough observations to justify them.

Correct Answer
verified

Autocorrelation of the residuals may affect the reliability of the t values for the estimated coefficients of the predictors X₁,X₂,... ,X_k.

Correct Answer
verified

The model Y = β₀ + β₁X + β₂X² cannot be estimated by Excel because of the nonlinear term.

Correct Answer
verified

Correct Answer
verified