Exam 14: Introduction to Multiple Regression
Exam 1: Introduction145 Questions
Exam 2: Organizing and Visualizing Data210 Questions
Exam 3: Numerical Descriptive Measures153 Questions
Exam 4: Basic Probability171 Questions
Exam 5: Discrete Probability Distributions218 Questions
Exam 6: The Normal Distribution and Other Continuous Distributions191 Questions
Exam 7: Sampling and Sampling Distributions197 Questions
Exam 8: Confidence Interval Estimation196 Questions
Exam 9: Fundamentals of Hypothesis Testing: One-Sample Tests165 Questions
Exam 10: Two-Sample Tests210 Questions
Exam 11: Analysis of Variance213 Questions
Exam 12: Chi-Square Tests and Nonparametric Tests201 Questions
Exam 13: Simple Linear Regression213 Questions
Exam 14: Introduction to Multiple Regression355 Questions
Exam 15: Multiple Regression Model Building96 Questions
Exam 16: Time-Series Forecasting168 Questions
Exam 17: Statistical Applications in Quality Management133 Questions
Exam 18: A Roadmap for Analyzing Data54 Questions
Exam 19: Questions that Involve Online Topics321 Questions
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TABLE 14-17
Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy)and the independent variables are the age of the worker (Age),the number of years of education received (Edu),the number of years at the previous job (Job Yr),a dummy variable for marital status (Married: 1 = married,0 = otherwise),a dummy variable for head of household (Head: 1 = yes,0 = no)and a dummy variable for management position (Manager: 1 = yes,0 = no).We shall call this Model 1.The coefficients of partial determination (R
)of each of the 6 predictors are,respectively,0.2807,0.0386,0.0317,0.0141,0.0958,and 0.1201.
Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are
Age and Manager.The results of the regression analysis are given below:
-Referring to Table 14-17 and using both Model 1 and Model 2,what is the value of the test statistic for testing whether the independent variables that are not significant individually are also not significant as a group in explaining the variation in the dependent variable at a 5% level of significance?



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TABLE 14-16
What are the factors that determine the acceleration time (in sec.)from 0 to 60 miles per hour of a car? Data on the following variables for 171 different vehicle models were collected:
Accel Time: Acceleration time in sec.
Cargo Vol: Cargo volume in cu.ft.
HP: Horsepower
MPG: Miles per gallon
SUV: 1 if the vehicle model is an SUV with Coupe as the base when SUV and Sedan are both 0
Sedan: 1 if the vehicle model is a sedan with Coupe as the base when SUV and Sedan are both 0
The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.
The various residual plots are as shown below.
The coefficients of partial determination (R
)of each of the 5 predictors are,respectively,0.0380,0.4376,0.0248,0.0188,and 0.0312.
The coefficient of multiple determination for the regression model using each of the 5 variables Xⱼ as the dependent variable and all other X variables as independent variables (R
)are,respectively,0.7461,0.5676,0.6764,0.8582,0.6632.
-Referring to 14-16,what is the p-value of the test statistic to determine whether Cargo Vol makes a significant contribution to the regression model in the presence of the other independent variables at a 5% level of significance?








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TABLE 14-15
The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test.She obtained the data on percentage of students passing the proficiency test (% Passing),daily mean of the percentage of students attending class (% Attendance),mean teacher salary in dollars (Salaries),and instructional spending per pupil in dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,X₁ = % Attendance,X₂= Salaries and X₃= Spending:
-Referring to Table 14-15,there is sufficient evidence that at least one of the explanatory variables is related to the percentage of students passing the proficiency test at a 5% level of significance.

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TABLE 14-5
A microeconomist wants to determine how corporate sales are influenced by capital and wage spending by companies.She proceeds to randomly select 26 large corporations and record information in millions of dollars.The Microsoft Excel output below shows results of this multiple regression.
-Referring to Table 14-5,one company in the sample had sales of $21.439 billion (Sales = 21,439).This company spent $300 million on capital and $700 million on wages.What is the residual (in millions of dollars)for this data point?

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TABLE 14-17
Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy)and the independent variables are the age of the worker (Age),the number of years of education received (Edu),the number of years at the previous job (Job Yr),a dummy variable for marital status (Married: 1 = married,0 = otherwise),a dummy variable for head of household (Head: 1 = yes,0 = no)and a dummy variable for management position (Manager: 1 = yes,0 = no).We shall call this Model 1.The coefficients of partial determination (R
)of each of the 6 predictors are,respectively,0.2807,0.0386,0.0317,0.0141,0.0958,and 0.1201.
Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are
Age and Manager.The results of the regression analysis are given below:
-Referring to Table 14-17 Model 1,which of the following is the correct null hypothesis to test whether age has any effect on the number of weeks a worker is unemployed due to a layoff while holding constant the effect of all the other independent variables?



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TABLE 14-4
A real estate builder wishes to determine how house size (House)is influenced by family income (Income),family size (Size),and education of the head of household (School).House size is measured in hundreds of square feet,income is measured in thousands of dollars,and education is in years.The builder randomly selected 50 families and ran the multiple regression.Microsoft Excel output is provided below:
-Referring to Table 14-4,what is the predicted house size (in hundreds of square feet)for an individual earning an annual income of $40,000,having a family size of 4,and going to school a total of 13 years?

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TABLE 14-16
What are the factors that determine the acceleration time (in sec.)from 0 to 60 miles per hour of a car? Data on the following variables for 171 different vehicle models were collected:
Accel Time: Acceleration time in sec.
Cargo Vol: Cargo volume in cu.ft.
HP: Horsepower
MPG: Miles per gallon
SUV: 1 if the vehicle model is an SUV with Coupe as the base when SUV and Sedan are both 0
Sedan: 1 if the vehicle model is a sedan with Coupe as the base when SUV and Sedan are both 0
The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.
The various residual plots are as shown below.
The coefficients of partial determination (R
)of each of the 5 predictors are,respectively,0.0380,0.4376,0.0248,0.0188,and 0.0312.
The coefficient of multiple determination for the regression model using each of the 5 variables Xⱼ as the dependent variable and all other X variables as independent variables (R
)are,respectively,0.7461,0.5676,0.6764,0.8582,0.6632.
-Referring to 14-16,what is the correct interpretation for the estimated coefficient for Cargo Vol?








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TABLE 14-10
You worked as an intern at We Always Win Car Insurance Company last summer.You notice that individual car insurance premiums depend very much on the age of the individual,the number of traffic tickets received by the individual,and the population density of the city in which the individual lives.You performed a regression analysis in Excel and obtained the following information:
-Referring to Table 14-10,to test the significance of the multiple regression model,what are the degrees of freedom?

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TABLE 14-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y).To provide its customers with information on that matter,a large real estate firm used the following 4 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X₁)the amount of insulation in inches (X₂),the number of windows in the house (X₃),and the age of the furnace in years (X₄).Given below are the Excel outputs of two regression models.
Model 1
Model 2
-Referring to Table 14-6,what is the value of the partial F test statistic for H₀: β₃ = β₄ = 0 vs.H₁: At least one βⱼ ≠ 0,j = 3,4?


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TABLE 14-16
What are the factors that determine the acceleration time (in sec.)from 0 to 60 miles per hour of a car? Data on the following variables for 171 different vehicle models were collected:
Accel Time: Acceleration time in sec.
Cargo Vol: Cargo volume in cu.ft.
HP: Horsepower
MPG: Miles per gallon
SUV: 1 if the vehicle model is an SUV with Coupe as the base when SUV and Sedan are both 0
Sedan: 1 if the vehicle model is a sedan with Coupe as the base when SUV and Sedan are both 0
The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.
The various residual plots are as shown below.
The coefficients of partial determination (R
)of each of the 5 predictors are,respectively,0.0380,0.4376,0.0248,0.0188,and 0.0312.
The coefficient of multiple determination for the regression model using each of the 5 variables Xⱼ as the dependent variable and all other X variables as independent variables (R
)are,respectively,0.7461,0.5676,0.6764,0.8582,0.6632.
-Referring to 14-16,the error appears to be left-skewed.








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TABLE 14-15
The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test.She obtained the data on percentage of students passing the proficiency test (% Passing),daily mean of the percentage of students attending class (% Attendance),mean teacher salary in dollars (Salaries),and instructional spending per pupil in dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,X₁ = % Attendance,X₂= Salaries and X₃= Spending:
-Referring to Table 14-15,which of the following is a correct statement?

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TABLE 14-18
A logistic regression model was estimated in order to predict the probability that a randomly chosen university or college would be a private university using information on mean total Scholastic Aptitude Test score (SAT)at the university or college,the room and board expense measured in thousands of dollars (Room/Brd),and whether the TOEFL criterion is at least 550 (Toefl550 = 1 if yes,0 otherwise.)The dependent variable,Y,is school type (Type = 1 if private and 0 otherwise).
The Minitab output is given below:
-Referring to Table 14-18,there is not enough evidence to conclude that the model is not a good-fitting model at a 0.05 level of significance.

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TABLE 14-16
What are the factors that determine the acceleration time (in sec.)from 0 to 60 miles per hour of a car? Data on the following variables for 171 different vehicle models were collected:
Accel Time: Acceleration time in sec.
Cargo Vol: Cargo volume in cu.ft.
HP: Horsepower
MPG: Miles per gallon
SUV: 1 if the vehicle model is an SUV with Coupe as the base when SUV and Sedan are both 0
Sedan: 1 if the vehicle model is a sedan with Coupe as the base when SUV and Sedan are both 0
The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.
The various residual plots are as shown below.
The coefficients of partial determination (R
)of each of the 5 predictors are,respectively,0.0380,0.4376,0.0248,0.0188,and 0.0312.
The coefficient of multiple determination for the regression model using each of the 5 variables Xⱼ as the dependent variable and all other X variables as independent variables (R
)are,respectively,0.7461,0.5676,0.6764,0.8582,0.6632.
-Referring to 14-16,what is the p-value of the test statistic to determine whether MPG makes a significant contribution to the regression model in the presence of the other independent variables at a 5% level of significance?








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TABLE 14-16
What are the factors that determine the acceleration time (in sec.)from 0 to 60 miles per hour of a car? Data on the following variables for 171 different vehicle models were collected:
Accel Time: Acceleration time in sec.
Cargo Vol: Cargo volume in cu.ft.
HP: Horsepower
MPG: Miles per gallon
SUV: 1 if the vehicle model is an SUV with Coupe as the base when SUV and Sedan are both 0
Sedan: 1 if the vehicle model is a sedan with Coupe as the base when SUV and Sedan are both 0
The regression results using acceleration time as the dependent variable and the remaining variables as the independent variables are presented below.
The various residual plots are as shown below.
The coefficients of partial determination (R
)of each of the 5 predictors are,respectively,0.0380,0.4376,0.0248,0.0188,and 0.0312.
The coefficient of multiple determination for the regression model using each of the 5 variables Xⱼ as the dependent variable and all other X variables as independent variables (R
)are,respectively,0.7461,0.5676,0.6764,0.8582,0.6632.
-Referring to 14-16,the 0 to 60 miles per hour acceleration time of an SUV is predicted to be 0.1252 seconds higher than that of a sedan.








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TABLE 14-7
The department head of the accounting department wanted to see if she could predict the GPA of students using the number of course units (credits)and total SAT scores of each.She takes a sample of students and generates the following Microsoft Excel output:
-Referring to Table 14-7,the department head wants to use a t test to test for the significance of the coefficient of X₁.For a level of significance of 0.05,the critical values of the test are ________.

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TABLE 14-19
The marketing manager for a nationally franchised lawn service company would like to study the characteristics that differentiate home owners who do and do not have a lawn service.A random sample of 30 home owners located in a suburban area near a large city was selected; 15 did not have a lawn service (code 0)and 15 had a lawn service (code 1).Additional information available concerning these 30 home owners includes family income (Income,in thousands of dollars),lawn size (Lawn Size,in thousands of square feet),attitude toward outdoor recreational activities (Atitude 0 = unfavorable,1 = favorable),number of teenagers in the household (Teenager),and age of the head of the household (Age).
The Minitab output is given below:
-Referring to Table 14-19,which of the following is the correct interpretation for the Income slope coefficient?

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TABLE 14-10
You worked as an intern at We Always Win Car Insurance Company last summer.You notice that individual car insurance premiums depend very much on the age of the individual,the number of traffic tickets received by the individual,and the population density of the city in which the individual lives.You performed a regression analysis in Excel and obtained the following information:
-Referring to Table 14-10,the estimated mean change in insurance premiums for every ?2 additional tickets received is ________.

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TABLE 14-15
The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test.She obtained the data on percentage of students passing the proficiency test (% Passing),daily mean of the percentage of students attending class (% Attendance),mean teacher salary in dollars (Salaries),and instructional spending per pupil in dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,X₁ = % Attendance,X₂= Salaries and X₃= Spending:
-Referring to Table 14-15,what is the standard error of estimate?

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TABLE 14-3
An economist is interested to see how consumption for an economy (in $ billions)is influenced by gross domestic product ($ billions)and aggregate price (consumer price index).The Microsoft Excel output of this regression is partially reproduced below.
-Referring to Table 14-3,what is the predicted consumption level for an economy with GDP equal to $4 billion and an aggregate price index of 150?

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TABLE 14-17
Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy)and the independent variables are the age of the worker (Age),the number of years of education received (Edu),the number of years at the previous job (Job Yr),a dummy variable for marital status (Married: 1 = married,0 = otherwise),a dummy variable for head of household (Head: 1 = yes,0 = no)and a dummy variable for management position (Manager: 1 = yes,0 = no).We shall call this Model 1.The coefficients of partial determination (R
)of each of the 6 predictors are,respectively,0.2807,0.0386,0.0317,0.0141,0.0958,and 0.1201.
Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are
Age and Manager.The results of the regression analysis are given below:
-Referring to Table 14-17 Model 1,which of the following is a correct statement?



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