Question 1

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2k different models.

Accepted Answer

A) True 
 B)False

Question 2

Large correlations between two or more independent variables in a multiple regression model could result in the problem of ___.

Accepted Answer

A) multicollinearity 
B) autocorrelation 
C) partial correlation 
D) rank correlation 
E) non-normality

Question 3

A multiple regression analysis produced the following tables:   Using $\alpha$ = 0.05 to test the null hypothesis H0: $\beta$1 = $\beta$2 = 0, the critical F value is ___.

Accepted Answer

A) 4.24 
B) 3.39 
C) 5.57 
D) 3.35 
E) 2.35

Question 4

If a square transformation is applied to a series of positive numbers greater than 1, the numerical values of the numbers in the transformed series will be smaller than the corresponding numbers in the original series.

Accepted Answer

A) True 
 B)False

Question 5

A multiple regression analysis produced the following tables:   These results indicate that ___.

Accepted Answer

A) none of the predictor variables is significant at the 5% level 
B) each predictor variable is significant at the 5% level 
C) x1 is the only predictor variable significant at the 5% level 
D) x12 is the only predictor variable significant at the 5% level 
E) each predictor variable is insignificant at the 5% level

Question 6

Abby Ross, a market specialist at the market research firm of Saez, Gann, and Spitz, is analyzing household budget data collected by her firm.Abby's dependent variable is monthly household expenditures on groceries (in $'s), and her independent variables are annual household income (in $1,000's)and household neighbourhood (0 = suburban, 1 = rural).Regression analysis of the data yielded the following table:  For a suburban household with $70,000 annual income, Abby's model predicts monthly grocery expenditure of ___.

Accepted Answer

A) $141.15 
B) $190.28 
C) $164.52 
D) $122.67 
E) $241.15

Question 7

Stepwise regression is one of the ways to prevent the problem of multicollinearity.

Accepted Answer

A) True 
 B)False

Question 8

A multiple regression analysis produced the following tables:   Using $\alpha$ = 0.10 to test the null hypothesis H0: $\beta$2 = 0, the critical t value is ___.

Accepted Answer

A) ± 1.316 
B) ± 1.314 
C) ± 1.703 
D) ± 1.780 
E) ± 1.708

Question 9

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2k - 1 different models.

Accepted Answer

A) True 
 B)False

Question 10

If a qualitative variable has "c" categories, how many dummy variables must be created and used in the regression analysis?

Accepted Answer

A) c - 1 
B) c 
C) c + 1 
D) c - 2 
E) 4 + c

Question 11

If two or more independent variables are highly correlated, the regression analysis might suffer from the problem of multicollinearity.

Accepted Answer

A) True 
 B)False

Question 12

A multiple regression analysis produced the following tables:   Using $\alpha$= 0.01 to test the null hypothesis H0: $\beta$1 = $\beta$2 = 0, the critical F value is ___.

Accepted Answer

A) 5.42 
B) 5.49 
C) 7.60 
D) 3.35 
E) 2.49

Question 13

Multiple linear regression models can handle certain nonlinear relationships by ___.

Accepted Answer

A) biasing the sample 
B) recoding or transforming variables 
C) adjusting the resultant ANOVA table 
D) adjusting the observed t and F values 
E) performing nonlinear regression

Question 14

Abby Ross, a market specialist at the market research firm of Saez, Gann, and Spitz, is analyzing household budget data collected by her firm.Abby's dependent variable is monthly household expenditures on groceries (in $'s), and her independent variables are annual household income (in $1,000's)and household neighbourhood (0 = suburban, 1 = rural).Regression analysis of the data yielded the following table:  For a rural household with $70,000 annual income, Abby's model predicts monthly grocery expenditure of ___.

Accepted Answer

A) $141.15 
B) $190.28 
C) $164.52 
D) $122.67 
E) $132.28

Question 15

The regression model y = $\beta$0 + $\beta$1 x1 + $\beta$2 x2 + $\beta$3 x1x2 + $\varepsilon$is a first-order model.

Accepted Answer

A) True 
 B)False

Question 16

Which of the following iterative search procedures for model building in a multiple regression analysis re-evaluates the contribution of variables previously included in the model after entering a new independent variable?

Accepted Answer

A) backward elimination 
B) stepwise regression 
C) forward selection 
D) all possible regressions 
E) backward selection

Question 17

A multiple regression analysis produced the following tables:   For x1= 10, the predicted value of y is ___.

Accepted Answer

A) 1,632.02 
B) 1,928.24 
C) 10.23 
D) 314.97 
E) 938.35

Question 18

Yvonne Lang, VP of Finance at Digital Components, Inc.(DCI), wants a regression model which predicts the average collection period on credit sales.Her data set includes two qualitative variables: sales discount rates (0%, 2%, 4%, and 6%), and total assets of credit customers (small, medium, and large).The number of dummy variables needed for "total assets of credit customer" in Yvonne's regression model is ___.

Accepted Answer

A) 1 
B) 2 
C) 3 
D) 4 
E) 7

Question 19

An "all possible regressions" search of a data set containing 4 independent variables will produce ___ regressions.

Accepted Answer

A) 15 
B) 12 
C) 8 
D) 4 
E) 2

Question 20

An "all possible regressions" search of a data set containing 9 independent variables will produce ___ regressions.

Accepted Answer

A) 9 
B) 18 
C) 115 
D) 151 
E) 511

Exam 14: Building Multiple Regression Models

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2^k different models.

Large correlations between two or more independent variables in a multiple regression model could result in the problem of ___.

If a square transformation is applied to a series of positive numbers greater than 1, the numerical values of the numbers in the transformed series will be smaller than the corresponding numbers in the original series.

A multiple regression analysis produced the following tables: These results indicate that ___.

Stepwise regression is one of the ways to prevent the problem of multicollinearity.

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2^k - 1 different models.

If a qualitative variable has "c" categories, how many dummy variables must be created and used in the regression analysis?

If two or more independent variables are highly correlated, the regression analysis might suffer from the problem of multicollinearity.

Multiple linear regression models can handle certain nonlinear relationships by ___.

The regression model y = $\beta$ ₀ + $\beta$ ₁ x₁ + $\beta$ ₂ x₂ + $\beta$ ₃ x₁x₂ + $\varepsilon$ is a first-order model.

Which of the following iterative search procedures for model building in a multiple regression analysis re-evaluates the contribution of variables previously included in the model after entering a new independent variable?

A multiple regression analysis produced the following tables: For x₁= 10, the predicted value of y is ___.

An "all possible regressions" search of a data set containing 4 independent variables will produce ___ regressions.

An "all possible regressions" search of a data set containing 9 independent variables will produce ___ regressions.

Exam 14: Building Multiple Regression Models

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2k different models.

Large correlations between two or more independent variables in a multiple regression model could result in the problem of ___.

A multiple regression analysis produced the following tables: Using α\alphaα = 0.05 to test the null hypothesis H0: β\betaβ 1 = β\betaβ 2 = 0, the critical F value is ___.

If a square transformation is applied to a series of positive numbers greater than 1, the numerical values of the numbers in the transformed series will be smaller than the corresponding numbers in the original series.

A multiple regression analysis produced the following tables: These results indicate that ___.

Stepwise regression is one of the ways to prevent the problem of multicollinearity.

A multiple regression analysis produced the following tables: Using α\alphaα = 0.10 to test the null hypothesis H0: β\betaβ 2 = 0, the critical t value is ___.

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2k - 1 different models.

If a qualitative variable has "c" categories, how many dummy variables must be created and used in the regression analysis?

If two or more independent variables are highly correlated, the regression analysis might suffer from the problem of multicollinearity.

A multiple regression analysis produced the following tables: Using α\alphaα = 0.01 to test the null hypothesis H0: β\betaβ 1 = β\betaβ 2 = 0, the critical F value is ___.

Multiple linear regression models can handle certain nonlinear relationships by ___.

The regression model y = β\betaβ 0 + β\betaβ 1 x1 + β\betaβ 2 x2 + β\betaβ 3 x1x2 + ε\varepsilonε is a first-order model.

Which of the following iterative search procedures for model building in a multiple regression analysis re-evaluates the contribution of variables previously included in the model after entering a new independent variable?

A multiple regression analysis produced the following tables: For x1= 10, the predicted value of y is ___.

An "all possible regressions" search of a data set containing 4 independent variables will produce ___ regressions.

An "all possible regressions" search of a data set containing 9 independent variables will produce ___ regressions.

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2^k different models.

If a data set contains k independent variables, the "all possible regression" search procedure will determine 2^k - 1 different models.

The regression model y = $\beta$ ₀ + $\beta$ ₁ x₁ + $\beta$ ₂ x₂ + $\beta$ ₃ x₁x₂ + $\varepsilon$ is a first-order model.

A multiple regression analysis produced the following tables: For x₁= 10, the predicted value of y is ___.