Exam 14: Introduction to Multiple Regression
Exam 1: Defining and Collecting Data189 Questions
Exam 3: Numerical Descriptive Measures184 Questions
Exam 4: Basic Probability156 Questions
Exam 5: Discrete Probability Distributions218 Questions
Exam 6: The Normal Distribution and Other Continuous Distributions189 Questions
Exam 7: Sampling Distributions127 Questions
Exam 8: Confidence Interval Estimation196 Questions
Exam 9: Fundamentals of Hypothesis Testing: One-Sample Tests170 Questions
Exam 10: Two-Sample Tests210 Questions
Exam 11: Analysis of Variance130 Questions
Exam 12: Chi-Square Tests and Nonparametric Tests175 Questions
Exam 13: Simple Linear Regression213 Questions
Exam 14: Introduction to Multiple Regression337 Questions
Exam 15: Multiple Regression Model Building96 Questions
Exam 16: Time-Series Forecasting165 Questions
Exam 17: A Roadmap for Analyzing Data303 Questions
Exam 18: Statistical Applications in Quality Management130 Questions
Exam 19: Decision Making126 Questions
Exam 20: Index Numbers44 Questions
Exam 21: Chi-Square Tests for the Variance or Standard Deviation11 Questions
Exam 22: Mcnemar Test for the Difference Between Two Proportions Related Samples15 Questions
Exam 25: The Analysis of Means Anom2 Questions
Exam 23: The Analysis of Proportions Anop3 Questions
Exam 24: The Randomized Block Design85 Questions
Exam 26: The Power of a Test41 Questions
Exam 27: Estimation and Sample Size Determination for Finite Populations13 Questions
Exam 28: Application of Confidence Interval Estimation in Auditing13 Questions
Exam 29: Sampling From Finite Populations20 Questions
Exam 30: The Normal Approximation to the Binomial Distribution27 Questions
Exam 31: Counting Rules14 Questions
Exam 32: Lets Get Started Big Things to Learn First33 Questions
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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; 11 did not have a lawn service (code 0)and 19 had a lawn service (code 1).Additional information available concerning these 30 home owners includes family income (Income,in thousands of dollars)and lawn size (Lawn Size,in thousands of square feet).
The PHStat output is given below:
-Referring to Table 14-19,what is the estimated probability that a home owner with a family income of $50,000 and a lawn size of 2,000 square feet will purchase a lawn service?

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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 and whether the TOEFL criterion is at least 90 (Toefl90 = 1 if yes,0 otherwise).The dependent variable,Y,is school type (Type = 1 if private and 0 otherwise).
The PHStat output is given below:
-Referring to Table 14-18,which of the following is the correct interpretation for the Toefl90 slope coefficient?

(Multiple Choice)
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TABLE 14-12
As a project for his business statistics class,a student examined the factors that determined parking meter rates throughout the campus area.Data were collected for the price ($)per hour of parking,blocks to the quadrangle,and whether the parking is on or off campus.The population regression model hypothesized is Yi = α + β1X1i + β2X2i + ε
where
Y is the meter price per hour.
X1 is the number of blocks to the quad.
X2 is a dummy variable that takes the value 1 if the meter is located on campus and 0 otherwise.
The following Excel results are obtained.
-Referring to Table 14-12,if one is already off campus but decides to park 3 more blocks from the quad,the estimated mean parking meter rate will decrease by ________.

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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; 11 did not have a lawn service (code 0)and 19 had a lawn service (code 1).Additional information available concerning these 30 home owners includes family income (Income,in thousands of dollars)and lawn size (Lawn Size,in thousands of square feet).
The PHStat output is given below:
-Referring to Table 14-19,what is the estimated odds ratio for a home owner with a family income of $100,000 and a lawn size of 5,000 square feet?

(Short Answer)
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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 30 different vehicle models were collected:
Y (Accel Time): Acceleration time in sec.
X1 (Engine Size): c.c.
X2 (Sedan): 1 if the vehicle model is a sedan and 0 otherwise
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 coefficient of partial determinations
and
are 0.3301,and 0.0594,respectively.
The coefficient of determination for the regression model using each of the 2 independent variables as the dependent variable and the other independent variable as independent variables (
)are,respectively 0.0077,and 0.0077.
-Referring to Table 14-16,what is the p-value of the test statistic to determine whether being a sedan or not makes a significant contribution to the regression model in the presence of the other independent variable at a 5% level of significance?








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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 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit (X1)and the amount of insulation in inches (X2).Given below is EXCEL output of the regression model.
Also SSR (X1 ∣ X2)= 8343.3572 and SSR (X2 ∣ X1)= 4199.2672
-True or False: The slopes in a multiple regression model are called net regression coefficients.

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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,one economy in the sample had an aggregate consumption level of $3 billion,a GDP of $3.5 billion,and an aggregate price level of 125.What is the residual for this data point?

(Multiple Choice)
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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 value of the adjusted coefficient of multiple determination,
,is ________.


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TABLE 14-4
A real estate builder wishes to determine how house size (House)is influenced by family income (Income)and family size (Size).House size is measured in hundreds of square feet and income is measured in thousands of dollars.The builder randomly selected 50 families and ran the multiple regression.Partial Microsoft Excel output is provided below:
Also SSR (X1 ∣ X2)= 36400.6326 and SSR (X2 ∣ X1)= 3297.7917
-Referring to Table 14-4,which of the following values for the level of significance is the smallest for which at most one explanatory variable is significant individually?

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TABLE 14-9
You decide to predict gasoline prices in different cities and towns in the United States for your term project.Your dependent variable is price of gasoline per gallon and your explanatory variables are per capita income and the number of firms that manufacture automobile parts in and around the city.You collected data of 32 cities and obtained a regression sum of squares SSR= 122.8821.Your computed value of standard error of the estimate is 1.9549.
-Referring to Table 14-9,if the variable that measures the number of firms that manufacture automobile parts in and around the city is removed from the multiple regression model,which of the following would be true?
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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)and a dummy variable for management position (Manager: 1 = yes,0 = no).
The results of the regression analysis are given below:
-Referring to Table 14-17,what are the numerator and denominator degrees of freedom,respectively,for the test statistic to determine whether there is a significant relationship between the number of weeks a worker is unemployed due to a layoff and the entire set of explanatory variables?

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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,the p-value for GDP is

(Multiple Choice)
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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),mean teacher salary in thousands of dollars (Salaries),and instructional spending per pupil in thousands of dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,X1 = Salaries and X2 = Spending:
-True or False: Referring to Table 14-15,the alternative hypothesis H1 : At least one of βj ≠ 0 for j = 1,2 implies that percentage of students passing the proficiency test is related to both of the explanatory variables.

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TABLE 14-13
An econometrician is interested in evaluating the relationship of demand for building materials to mortgage rates in Los Angeles and San Francisco.He believes that the appropriate model is
Y = 10 + 5X1 + 8X2
where X1 = mortgage rate in %
X2 = 1 if SF,0 if LA
Y = demand in $100 per capita
-Referring to Table 14-13,the predicted demand in Los Angeles when the mortgage rate is 8% is ________.
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TABLE 14-8
A financial analyst wanted to examine the relationship between salary (in $1,000)and 2 variables: age
(X1 = Age)and experience in the field (X2 = Exper).He took a sample of 20 employees and obtained the following Microsoft Excel output:
Also,the sum of squares due to the regression for the model that includes only Age is 5022.0654 while the sum of squares due to the regression for the model that includes only Exper is 125.9848.
-Referring to Table 14-8,the value of the adjusted coefficient of multiple determination 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),mean teacher salary in thousands of dollars (Salaries),and instructional spending per pupil in thousands of dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,X1 = Salaries and X2 = Spending:
-True or False: Referring to Table 14-15,there is sufficient evidence that the percentage of students passing the proficiency test depends on at least one of the explanatory variables at a 5% level of significance.

(True/False)
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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,when the microeconomist used a simple linear regression model with sales as the dependent variable and wages as the independent variable,she obtained an r2 value of 0.601.What additional percentage of the total variation of sales has been explained by including capital spending in the multiple regression?

(Multiple Choice)
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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,what is the p-value for testing whether Wages have a positive impact on corporate sales?

(Multiple Choice)
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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; 11 did not have a lawn service (code 0)and 19 had a lawn service (code 1).Additional information available concerning these 30 home owners includes family income (Income,in thousands of dollars)and lawn size (Lawn Size,in thousands of square feet).
The PHStat output is given below:
-Referring to Table 14-19,which of the following is the correct interpretation for the Income slope coefficient?

(Multiple Choice)
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