Question 1

A useful technique in controlling multicollinearity involves the ___.

Accepted Answer

A) use of variance inflation factors 
B) use of the backward elimination procedure 
C) use of the forward elimination procedure 
D) use of the forward selection procedure 
E) use of all possible regressions 
A) use of variance inflation factors 
B) use of the backward elimination procedure 
C) use of the forward elimination procedure 
D) use of the forward selection procedure 
E) use of all possible regressions A

Question 2

Abby Kratz,a market specialist at the market research firm of Saez,Sikes,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 
A) $141.15 
B) $190.28 
C) $164.52 
D) $122.67 
E) $241.15 A

Question 3

Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable that will be entered into the regression model by the forward selection procedure will be ___.

Accepted Answer

A) x1 
B) x2 
C) x3 
D) x4 
E) x5 
A) x1 
B) x2 
C) x3 
D) x4 
E) x5 A

Question 4

Abby Kratz,a market specialist at the market research firm of Saez,Sikes,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:   Abby's model is ___.

Accepted Answer

A) y = 19.68247 + 10.01176 x1 + 1.965934 x2 
B) y = 1.965934 + 9.940612 x1 + 6.416667 x2 
C) y = 10.01176 + 0.174564 x1 + 7.655776 x2 
D) y = 19.68247 - 1.735272 x1 + 49.12456 x2 
E) y = 19.68247 + 1.735272 x1 + 49.12456 x2 
A) y = 19.68247 + 10.01176 x1 + 1.965934 x2 
B) y = 1.965934 + 9.940612 x1 + 6.416667 x2 
C) y = 10.01176 + 0.174564 x1 + 7.655776 x2 
D) y = 19.68247 - 1.735272 x1 + 49.12456 x2 
E) y = 19.68247 + 1.735272 x1 + 49.12456 x2

Question 5

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

Accepted Answer

A) ± 1.311 
B) ± 1.699 
C) ± 1.703 
D) ± 2.502 
E) ± 2.052 
A) ± 1.311 
B) ± 1.699 
C) ± 1.703 
D) ± 2.502 
E) ± 2.052

Question 6

In multiple regression analysis,qualitative variables are sometimes referred to as ___.

Accepted Answer

A) dummy variables 
B) quantitative variables 
C) dependent variables 
D) performance variables 
E) cardinal variables 
A) dummy variables 
B) quantitative variables 
C) dependent variables 
D) performance variables 
E) cardinal variables

Question 7

Which of the following iterative search procedures for model building in a multiple regression analysis adds variables to the model as it proceeds,but does not re-evaluate the contribution of previously entered variables?

Accepted Answer

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

Question 8

A linear regression model cannot be used to explore the possibility that a quadratic relationship may exist between two variables.

Accepted Answer

A) True 
 B)False

Question 9

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 10

Alan Bissell,a market analyst for City Sound Mart,is analyzing sales of heavy metal CD's.Alan's dependent variable is annual heavy metal CD sales (in $1,000,000's),and his independent variables are teenage population (in 1,000's)and type of sales district (0 = urban,1 = rural).Regression analysis of the data yielded the following tables:   For a rural sales district with 10,000 teenagers,Alan's model predicts annual sales of heavy metal CD sales of ___.

Accepted Answer

A) $2,100,000 
B) $524,507 
C) $533,333 
D) $729,683 
E) $210,000 
A) $2,100,000 
B) $524,507 
C) $533,333 
D) $729,683 
E) $210,000

Question 11

The regression model y = $\beta$0 + $\beta$1 x1 + $\beta$2 x2 + $\beta$3 x3 + $\varepsilon$is a third order model.

Accepted Answer

A) True 
 B)False

Question 12

If the effect of an independent variable (e.g. ,humidity)on a dependent variable (e.g. ,hardness)is affected by different ranges of values for a second independent variable (e.g. ,temperature),the two independent variables are said to interact.

Accepted Answer

A) True 
 B)False

Question 13

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

Accepted Answer

A) 2k -1 
B) 2k-1 
C) k2 - 1 
D) 2k - 1 
E) 2k 
A) 2k -1 
B) 2k-1 
C) k2 - 1 
D) 2k - 1 
E) 2k

Question 14

Regression models in which the highest power of any predictor variable is 1 and in which there are no cross product terms are referred to as first-order models.

Accepted Answer

A) True 
 B)False

Question 15

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

Question 16

A qualitative variable which represents categories such as geographical territories or job classifications may be included in a regression model by using indicator or dummy variables.

Accepted Answer

A) True 
 B)False

Question 17

Recognize when multicollinearity is present,understanding general techniques for preventing and controlling it.

Accepted Answer

One of the problems in using multiple re

Question 18

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 19

Use all possible regressions,stepwise regression,forward selection,and backward elimination search procedures to develop regression models that account for the most variation in the dependent variable and are parsimonious.

Accepted Answer

You can build regression models in many

Question 20

A linear regression model can be used to explore the possibility that a quadratic relationship may exist between two variables by suitably transforming the independent variable.

Accepted Answer

A) True 
 B)False

A useful technique in controlling multicollinearity involves the ___.

Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable that will be entered into the regression model by the forward selection procedure will be ___.

In multiple regression analysis,qualitative variables are sometimes referred to as ___.

Which of the following iterative search procedures for model building in a multiple regression analysis adds variables to the model as it proceeds,but does not re-evaluate the contribution of previously entered variables?

A linear regression model cannot be used to explore the possibility that a quadratic relationship may exist between two variables.

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

The regression model y = $\beta$ ₀ + $\beta$ ₁ x₁ + $\beta$ ₂ x₂ + $\beta$ ₃ x₃ + $\varepsilon$ is a third order model.

If the effect of an independent variable (e.g. ,humidity)on a dependent variable (e.g. ,hardness)is affected by different ranges of values for a second independent variable (e.g. ,temperature),the two independent variables are said to interact.

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

Regression models in which the highest power of any predictor variable is 1 and in which there are no cross product terms are referred to as first-order models.

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

A qualitative variable which represents categories such as geographical territories or job classifications may be included in a regression model by using indicator or dummy variables.

Recognize when multicollinearity is present,understanding general techniques for preventing and controlling it.

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

Use all possible regressions,stepwise regression,forward selection,and backward elimination search procedures to develop regression models that account for the most variation in the dependent variable and are parsimonious.

A linear regression model can be used to explore the possibility that a quadratic relationship may exist between two variables by suitably transforming the independent variable.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

Exam 14: Building Multiple Regression Models

A useful technique in controlling multicollinearity involves the ___.

Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals that the first independent variable that will be entered into the regression model by the forward selection procedure will be ___.

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

In multiple regression analysis,qualitative variables are sometimes referred to as ___.

Which of the following iterative search procedures for model building in a multiple regression analysis adds variables to the model as it proceeds,but does not re-evaluate the contribution of previously entered variables?

A linear regression model cannot be used to explore the possibility that a quadratic relationship may exist between two variables.

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

The regression model y = β\betaβ 0 + β\betaβ 1 x1 + β\betaβ 2 x2 + β\betaβ 3 x3 + ε\varepsilonε is a third order model.

If the effect of an independent variable (e.g. ,humidity)on a dependent variable (e.g. ,hardness)is affected by different ranges of values for a second independent variable (e.g. ,temperature),the two independent variables are said to interact.

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

Regression models in which the highest power of any predictor variable is 1 and in which there are no cross product terms are referred to as first-order models.

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

A qualitative variable which represents categories such as geographical territories or job classifications may be included in a regression model by using indicator or dummy variables.

Recognize when multicollinearity is present,understanding general techniques for preventing and controlling it.

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.

Use all possible regressions,stepwise regression,forward selection,and backward elimination search procedures to develop regression models that account for the most variation in the dependent variable and are parsimonious.

A linear regression model can be used to explore the possibility that a quadratic relationship may exist between two variables by suitably transforming the independent variable.

Introduction to Statistics

Charts and Graphs

Descriptive Statistics

Probability

Discrete Distributions

Continuous Distributions

Sampling and Sampling Distributions

Statistical Inference: Estimation for Single Populations

Statistical Inference: Hypothesis Testing for Single Populations

Statistical Inferences About Two Populations

Analysis of Variance and Design of Experiments

Simple Regression Analysis and Correlation

Multiple Regression Analysis

Time-Series Forecasting and Index Numbers

Analysis of Categorical Data

Nonparametric Statistics

Statistical Quality Control

Decision Analysis

Filters

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

The regression model y = $\beta$ ₀ + $\beta$ ₁ x₁ + $\beta$ ₂ x₂ + $\beta$ ₃ x₃ + $\varepsilon$ is a third order model.

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