Question 1

The regression model y = $\beta$0 + $\beta$1 x1 + $\beta$2 x21 + $\varepsilon$ is called a quadratic model.

Accepted Answer

A) True 
 B)False

Question 2

Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________.

Accepted Answer

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

Question 3

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 weekly household expenditures on groceries (in $'s),and her independent variables are annual household income (in $1,000's)and household neighborhood (0 = suburban,1 = rural).Regression analysis of the data yielded the following table.   For a rural household with ______ annual income,Abby's model predicts weekly grocery expenditure of $235.

Accepted Answer

A)  $90,753.44 
B)  $92,257.51 
C)  $94,734.77 
D)  $95,773.44 
E)  $96,737.71 
A)  $90,753.44 
B)  $92,257.51 
C)  $94,734.77 
D)  $95,773.44 
E)  $96,737.71

Question 4

A multiple regression analysis produced the following tables.     The regression equation for this analysis is ____________.

Accepted Answer

A)  y = 762.1533 + 96.8433 x1 + 3.007943 x12 
B)  y = 1411.876 + 762.1533 x1 + 1.852483 x12 
C)  y = 1411.876 + 35.18215 x1 + 7.721648 x12 
D)  y = 762.1533 + 1.852483 x1 + 0.074919 x12 
E)  y = 762.1533 - 1.852483 x1 + 0.074919 x12 
A)  y = 762.1533 + 96.8433 x1 + 3.007943 x12 
B)  y = 1411.876 + 762.1533 x1 + 1.852483 x12 
C)  y = 1411.876 + 35.18215 x1 + 7.721648 x12 
D)  y = 762.1533 + 1.852483 x1 + 0.074919 x12 
E)  y = 762.1533 - 1.852483 x1 + 0.074919 x12

Question 5

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 6

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 weekly household expenditures on groceries (in $'s),and her independent variables are annual household income (in $1,000's)and household neighborhood (0 = suburban,1 = rural). Regression analysis of the data yielded the following table.   For two households,one suburban and one rural,Abby's model predicts ________.

Accepted Answer

A)  equal weekly expenditures for groceries 
B)  the suburban household's weekly expenditures for groceries will be $49 more 
C)  the rural household's weekly expenditures for groceries will be $49 more 
D)  the suburban household's weekly expenditures for groceries will be $8 more 
E)  the rural household's weekly expenditures for groceries will be $49 less 
A)  equal weekly expenditures for groceries 
B)  the suburban household's weekly expenditures for groceries will be $49 more 
C)  the rural household's weekly expenditures for groceries will be $49 more 
D)  the suburban household's weekly expenditures for groceries will be $8 more 
E)  the rural household's weekly expenditures for groceries will be $49 less

Question 7

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)  8.09 
B)  6.89 
C)  6.09 
D)  5.78 
E)  5.09 
A)  8.09 
B)  6.89 
C)  6.09 
D)  5.78 
E)  5.09

Question 8

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 9

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

Question 10

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

Accepted Answer

A) True 
 B)False

Question 11

The interaction between two independent variables can be examined by including a new variable,which is the sum of the two independent variables,in the regression model.

Accepted Answer

A) True 
 B)False

Question 12

A multiple regression analysis produced the following tables.     If the predicted value of the dependent variable is 1000,then x1 = ______.

Accepted Answer

A)  7.928666 
B)  8.158666 
C)  9.928668 
D)  10.15866 
E)  11.928666 
A)  7.928666 
B)  8.158666 
C)  9.928668 
D)  10.15866 
E)  11.928666

Question 13

Carlos Cavazos,Director of Human Resources,is exploring employee absenteeism at the Plano Piano Plant.A multiple regression analysis was performed using the following variables.The results are presented below.         Which of the following conclusions can be drawn from the above results?

Accepted Answer

A)  All the independent variables in the regression are significant at 5% level. 
B)  Commuting distance is a highly significant (<1%) variable in explaining absenteeism. 
C)  Age of the employees tends to have a very significant (<1%) effect on absenteeism. 
D)  This model explains a little over 49% of the variability in absenteeism data. 
E)  A single-parent household employee is expected to be absent less number of days all other variables held constant compared to one who is not a single-parent household. 
A)  All the independent variables in the regression are significant at 5% level. 
B)  Commuting distance is a highly significant (<1%) variable in explaining absenteeism. 
C)  Age of the employees tends to have a very significant (<1%) effect on absenteeism. 
D)  This model explains a little over 49% of the variability in absenteeism data. 
E)  A single-parent household employee is expected to be absent less number of days all other variables held constant compared to one who is not a single-parent household.

Question 14

An acceptable method of managing multicollinearity in a regression model is the ___.

Accepted Answer

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

Question 15

Hope Hernandez is the new regional Vice President for a large gasoline station chain.She wants a regression model to predict sales in the convenience stores. Her data set includes two qualitative variables: the gasoline station location (inner city,freeway,and suburbs),and curb appeal of the convenience store (low,medium,and high).The number of dummy variables needed for Hope's regression model is ______.

Accepted Answer

A)  2 
B)  4 
C)  6 
D)  8 
E)  9 
A)  2 
B)  4 
C)  6 
D)  8 
E)  9

Question 16

A local parent group was concerned with the increasing school cost for families with school aged children.The parent group was interested in understanding the relationship between the
The academic grade level for the child and the total costs spent per child per academic year.They
Performed a multiple regression analysis using total cost as the dependent variable and academic
Year (x1)as the independent variables.The multiple regression analysis produced the following
Tables.
    For a child in grade 10 (x1= 10)the predicted value of y is ____________.

Accepted Answer

A)  707.91 
B)  1,117.38 
C)  856.08 
D)  2,189.54 
E)  1,928.24 
A)  707.91 
B)  1,117.38 
C)  856.08 
D)  2,189.54 
E)  1,928.24

Question 17

A logarithmic transformation may be applied to both positive and negative numbers.

Accepted Answer

A) True 
 B)False

Question 18

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 19

A research project was conducted to study the effect of a chemical on undesired insects.The researcher uses 6 dose levels,and at each level exposes 250 insects to the chemical and proceeds to count the number of insects that die.The researcher uses a binary logistic regression model to estimate the probability of death as a function of dose. Shown below is Minitab output from a logistic regression.
Coefficients
Term Coef SE Coef 95% CI Z-Value P-Value VIF
Constant -2.644 0.156 (-2.950,-2.338) -16.94 0.000
Dose 0.6740 0.0391 (0.5973,0.7506) 17.23 0.000 1.00
Odd Ratios for Continuous Predictors
Odds Ratio 95% CI
Dose 1.9621 (1.8173,2.1184)
The predicted probability that an insect will die when exposed to the second dose is ____.

Accepted Answer

A)  0.1246 
B)  0.1446 
C)  0.1857 
D)  0.2737 
E)  0.2945 
A)  0.1246 
B)  0.1446 
C)  0.1857 
D)  0.2737 
E)  0.2945

Question 20

The following scatter plot indicates that _________.

Accepted Answer

A)  a x2 transform may be useful 
B)  a log y transform may be useful 
C)  a x4 transform may be useful 
D)  no transform is needed 
E)  a x3 transform may be useful 
A)  a x2 transform may be useful 
B)  a log y transform may be useful 
C)  a x4 transform may be useful 
D)  no transform is needed 
E)  a x3 transform may be useful

The regression model y = $\beta$ ₀ + $\beta$ ₁ x₁ + $\beta$ ₂ x²₁ + $\varepsilon$ is called a quadratic model.

Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________.

A multiple regression analysis produced the following tables. The regression equation for this analysis is ____________.

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

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.

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

The interaction between two independent variables can be examined by including a new variable,which is the sum of the two independent variables,in the regression model.

A multiple regression analysis produced the following tables. If the predicted value of the dependent variable is 1000,then x₁ = ______.

Carlos Cavazos,Director of Human Resources,is exploring employee absenteeism at the Plano Piano Plant.A multiple regression analysis was performed using the following variables.The results are presented below. Which of the following conclusions can be drawn from the above results?

An acceptable method of managing multicollinearity in a regression model is the ___.

A logarithmic transformation may be applied to both positive and negative numbers.

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.

The following scatter plot indicates that _________.

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

A Nalysis 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

The regression model y = β\betaβ 0 + β\betaβ 1 x1 + β\betaβ 2 x21 + ε\varepsilonε is called a quadratic model.

Inspection of the following table of correlation coefficients for variables in a multiple regression analysis reveals potential multicollinearity with variables ___________.

A multiple regression analysis produced the following tables. The regression equation for this analysis is ____________.

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.

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 ______.

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.

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 ____.

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

The interaction between two independent variables can be examined by including a new variable,which is the sum of the two independent variables,in the regression model.

A multiple regression analysis produced the following tables. If the predicted value of the dependent variable is 1000,then x1 = ______.

Carlos Cavazos,Director of Human Resources,is exploring employee absenteeism at the Plano Piano Plant.A multiple regression analysis was performed using the following variables.The results are presented below. Which of the following conclusions can be drawn from the above results?

An acceptable method of managing multicollinearity in a regression model is the ___.

A logarithmic transformation may be applied to both positive and negative numbers.

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.

The following scatter plot indicates that _________.

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

A Nalysis 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

The regression model y = $\beta$ ₀ + $\beta$ ₁ x₁ + $\beta$ ₂ x²₁ + $\varepsilon$ is called a quadratic model.

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. If the predicted value of the dependent variable is 1000,then x₁ = ______.