Question 1

Regression models that employ more than one independent variable are referred to as multiple regression models.

Accepted Answer

A) True 
 B)False

Question 2

Consider the following partial computer output for a multiple regression model.

Accepted Answer

\[\begin{array} { l c c } 
\underline{\t

Question 3

A multiple regression model with 3 independent variables and 16 observations produced the following analysis of variance table.

Accepted Answer

\[\begin{array} { l l l l l } 
\text { S

Question 4

For a given multiple regression model with three independent variables,the value of the adjusted multiple coefficient of determination is _________ less than R2.

Accepted Answer

A) Always 
B) Sometimes 
C) Never 
A) Always 
B) Sometimes 
C) Never

Question 5

The management of a professional baseball team is in the process of determining the budget for next year.A major component of future revenue is attendance at the home games.In order to predict attendance at home games the team statistician has used a multiple regression model with dummy variables.The model is of the form y = β0 + β1x1 + β2x2 + β3x3 + ε,where:
y = attendance at a home game.
x1 = current power rating of the team on a scale from 0 to 100 before the game.
x2 and x3 are dummy variables,and they are defined below.
x2 = 1,if weekend,
x2 = 0,otherwise.
x3 = 1,if weather is favorable,
x3 = 0,otherwise.
After collecting the data,based on 30 games from last year,and implementing the above stated multiple regression model,the team statistician obtained the following least squares multiple regression equation:

Accepted Answer

@#LAT-DLM& 
The multiple regression compute output

Question 6

Which one of the following is not a tool used to identify multicollinearity?

Accepted Answer

A) Variance inflation factor 
B) Correlation matrix 
C) Studentized residuals 
D) Scatter plots that show all combinations of variables in the regression model 
A) Variance inflation factor 
B) Correlation matrix 
C) Studentized residuals 
D) Scatter plots that show all combinations of variables in the regression model

Question 7

Below is a portion of a logistic regression table showing the probability of an employee leaving his or her current position:

Accepted Answer

\[\begin{array} { l l l } 
\text { Predi

Question 8

Below is a partial multiple regression computer output based on a quadratic regression model.

Accepted Answer

\[\begin{array} { l l l } 
\text { Sourc

Question 9

The management of a professional baseball team is in the process of determining the budget for next year.A major component of future revenue is attendance at the home games.In order to predict attendance at home games,the team statistician has used a multiple regression model with dummy variables.The model is of the form y = β0 + β1x1 + β2x2 + β3x3 + ε,where:
y = attendance at a home game.
x1 = current power rating of the team on a scale from 0 to 100 before the game.
x2 and x3 are dummy variables,and they are defined below.
x2 = 1,if weekend,
x2 = 0,otherwise.
x3 = 1,if weather is favorable,
x3 = 0,otherwise.
After collecting the data,based on 30 games from last year,and implementing the above stated multiple regression model,the team statistician obtained the following least squares multiple regression equation:

Accepted Answer

@#LAT-DLM& 
The multiple regression computer outpu

Question 10

A member of the state legislature has expressed concern about the differences in the mathematics test scores of high school freshmen across the state.She asks her research assistant to conduct a study to investigate what factors could account for the differences.The research assistant looks at a random sample of school districts across the state and uses the factors of percentage of mathematics teachers in each district with a degree in mathematics,the average age of mathematics teachers,and the average salary of mathematics teachers.

Accepted Answer

\[\begin{array}{l}
\begin{array} { l r r

Question 11

When the F test is used to test the overall significance of a multiple regression model,if the null hypothesis is rejected,it can be concluded that all of the independent variables x1,x2,... ,xk are significantly related to the dependent variable y.

Accepted Answer

A) True 
 B)False

Question 12

Below is a partial multiple regression computer output based on a quadratic regression model.

Accepted Answer

\[\begin{array} { l l l } 
\text { Sourc

Question 13

The manufacturer of a light fixture believes that the dollars spent on advertising,the price of the fixture and the number of retail stores selling the fixture in a particular month influence the light fixture sales.The manufacturer randomly selects 10 months and collects the following data:

Accepted Answer

The sales are in thousands of units per

Question 14

An investigator hired by a client suing for sex discrimination has developed a multiple regression model for employee salaries for the company in question.In this multiple regression model,the salaries are in thousands of dollars.For example,a data entry of 35 for the dependent variable indicates a salary of $35,000.The indicator (dummy)variable for gender is coded as X1 = 0 if male and X1 = 1 if female.The computer output of this multiple regression model shows that the coefficient for this variable (X1)is -4.2.The t test showed that X1 was significant at α = 0.1.This result implies that for male and female workers of the company,

Accepted Answer

A) On the average,females earn $4200 less. 
B) On the average,males earn $4200 less. 
C) On the average,salaries do not differ. 
D) On the average,males have 4.2 more years of experience. 
E) On the average,females have 4.2 more years of experiencE. 
A) On the average,females earn $4200 less. 
B) On the average,males earn $4200 less. 
C) On the average,salaries do not differ. 
D) On the average,males have 4.2 more years of experience. 
E) On the average,females have 4.2 more years of experiencE.

Question 15

The graph of the prediction equation obtained from the model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 1 } ^ { 2 } + \varepsilon$
Is a(n)____________.

Accepted Answer

A) Line 
B) Plane 
C) Parabola 
D) Exponential curve 
A) Line 
B) Plane 
C) Parabola 
D) Exponential curve

Question 16

Consider the following partial computer output for a multiple regression model.

Accepted Answer

\[\begin{array} { l l l } 
\text { Predi

Question 17

In a regression model,a value of the error term depends upon other values of the error term.

Accepted Answer

A) True 
 B)False

Question 18

Multicollinearity is severe if the largest variance inflation factor (VIF)is greater than _____.

Accepted Answer

A) 100 
B) 5 
C) 10 
D) 1 
A) 100 
B) 5 
C) 10 
D) 1

Question 19

The management of a professional baseball team is in the process of determining the budget for next year.A major component of future revenue is attendance at the home games.In order to predict attendance at home games,the team statistician has used a multiple regression model with dummy variables.The model is of the form y = β0 + β1x1 + β2x2 + β3x3 + ε,where:
y = attendance at a home game.
x1 = current power rating of the team on a scale from 0 to 100 before the game.
x2 and x3 are dummy variables,and they are defined below.
x2 = 1,if weekend,
x2 = 0,otherwise.
x3 = 1,if weather is favorable,
x3 = 0,otherwise.
After collecting the data,based on 30 games from last year,and implementing the above stated multiple regression model,the team statistician obtained the following least squares multiple regression equation:

Accepted Answer

@#LAT-DLM& 
The multiple regression computer outpu

Question 20

The graph of the prediction equation obtained from the model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 2 } + \varepsilon$
Is a(n)__________.

Accepted Answer

A) Line 
B) Plane 
C) Parabola 
D) Exponential curve 
A) Line 
B) Plane 
C) Parabola 
D) Exponential curve

Regression models that employ more than one independent variable are referred to as multiple regression models.

Consider the following partial computer output for a multiple regression model.

A multiple regression model with 3 independent variables and 16 observations produced the following analysis of variance table.

For a given multiple regression model with three independent variables,the value of the adjusted multiple coefficient of determination is _________ less than R².

Which one of the following is not a tool used to identify multicollinearity?

Below is a portion of a logistic regression table showing the probability of an employee leaving his or her current position:

Below is a partial multiple regression computer output based on a quadratic regression model.

When the F test is used to test the overall significance of a multiple regression model,if the null hypothesis is rejected,it can be concluded that all of the independent variables x₁,x₂,... ,x_k are significantly related to the dependent variable y.

Below is a partial multiple regression computer output based on a quadratic regression model.

The manufacturer of a light fixture believes that the dollars spent on advertising,the price of the fixture and the number of retail stores selling the fixture in a particular month influence the light fixture sales.The manufacturer randomly selects 10 months and collects the following data:

The graph of the prediction equation obtained from the model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 1 } ^ { 2 } + \varepsilon$ Is a(n)____________.

Consider the following partial computer output for a multiple regression model.

In a regression model,a value of the error term depends upon other values of the error term.

Multicollinearity is severe if the largest variance inflation factor (VIF)is greater than _____.

The graph of the prediction equation obtained from the model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 2 } + \varepsilon$ Is a(n)__________.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Time Series Forecasting and Index Numbers

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

Exam 15: Multiple Regression and Model Building

Regression models that employ more than one independent variable are referred to as multiple regression models.

Consider the following partial computer output for a multiple regression model.

A multiple regression model with 3 independent variables and 16 observations produced the following analysis of variance table.

For a given multiple regression model with three independent variables,the value of the adjusted multiple coefficient of determination is _________ less than R2.

Which one of the following is not a tool used to identify multicollinearity?

Below is a portion of a logistic regression table showing the probability of an employee leaving his or her current position:

Below is a partial multiple regression computer output based on a quadratic regression model.

When the F test is used to test the overall significance of a multiple regression model,if the null hypothesis is rejected,it can be concluded that all of the independent variables x1,x2,... ,xk are significantly related to the dependent variable y.

Below is a partial multiple regression computer output based on a quadratic regression model.

The manufacturer of a light fixture believes that the dollars spent on advertising,the price of the fixture and the number of retail stores selling the fixture in a particular month influence the light fixture sales.The manufacturer randomly selects 10 months and collects the following data:

The graph of the prediction equation obtained from the model y=β0+β1X1+β2X12+ε\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 1 } ^ { 2 } + \varepsilony=β0​+β1​X1​+β2​X12​+ε Is a(n)____________.

Consider the following partial computer output for a multiple regression model.

In a regression model,a value of the error term depends upon other values of the error term.

Multicollinearity is severe if the largest variance inflation factor (VIF)is greater than _____.

The graph of the prediction equation obtained from the model y=β0+β1X1+β2X2+ε\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 2 } + \varepsilony=β0​+β1​X1​+β2​X2​+ε Is a(n)__________.

Statistical Inferences for Population Variances

Experimental Design and Analysis of Variance

Chi-Square Tests

Simple Linear Regression Analysis

Time Series Forecasting and Index Numbers

Process Improvement Using Control Charts

Nonparametric Methods

Decision Theory

Filters

For a given multiple regression model with three independent variables,the value of the adjusted multiple coefficient of determination is _________ less than R².

When the F test is used to test the overall significance of a multiple regression model,if the null hypothesis is rejected,it can be concluded that all of the independent variables x₁,x₂,... ,x_k are significantly related to the dependent variable y.

The graph of the prediction equation obtained from the model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 1 } ^ { 2 } + \varepsilon$ Is a(n)____________.

The graph of the prediction equation obtained from the model $\mathrm { y } = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 2 } + \varepsilon$ Is a(n)__________.