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Unformatted text preview: he quantitative independent variables include the age of the
patient, cholesterol level of the patient, and blood pressure of the patient. Define the dummy
variables so that all other hospitals are compared to the City hospital (base).
x1 = 1, if the heart surgery is in Regional Memorial Hospital
x1 = 0, otherwise
x2 = 1, if the heart surgery is in General Hospital
x2 = 0, otherwise
x3 = 1, if the heart surgery is in Charity Hospital
x3 = 0, otherwise AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: Logistic 86. A county has four major hospitals: 1) Regional Memorial; 2) General; 3) Charity; and 4)
City. A multiple regression model is used to compare the time spent in the hospital after a
heart bypass surgery among the four hospitals. The response (dependent) variable is the
amount of time spent in the hospital (in days). The variables used to predict the time spent in
the hospital include the patient's age, cholesterol level (in mlg.), blood pressure, as well as
variables indicating the hospital in which the surgery was performed. Determine the total
number of independent variables in the multiple regression model. Indicate how many of
these are quantitative variables and how many are indicator (dummy) variables.
6 independent variables (3 quantitative, 3 dummy) AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 3
Topic: Logistic 11509 Chapter 01  An Introduction to Business Statistics 87. If the multiple coefficient of determination that relates x1 to all the other independent
variables, R2(x1) = .25, calculate the variance inflation factor for x1. Should the analyst be
concerned about multicollinearity? Why?
1.33. No, the analyst need not be concerned about multicollienarity because 1.33 < 10. AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 4
Topic: Multicollinearity 88. If the multiple coefficient of determination that relates x2 to all the other independent
variables, R2(x2) = .94, calculate the variance inflation factor for x2. Should the analyst be
concerned about multicollinearity? Why?
16.67. Yes, the analyst should be concerned about multicollinearity because 16.667 > 10. AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 4
Topic: Multicollinearity 11510 Chapter 01  An Introduction to Business Statistics 89. If the multiple coefficient of determination that relates x3 to all the other independent
variables, R2(x3) = .8, calculate the variance inflation factor for x3. Should the analyst be
concerned about multicollinearity? Why?
5.0. No, the analyst need not be concerned about multicollinearity because 5 < 10. AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 4
Topic: Multicollinearity 90. Calculate the studentized (standardized) residual where the residual is equal to 11.951 and
s is 14.8 and the leverage value (h) is equal to 0.0975.
.85 AACSB: Analytical Skills
Bloom's: Application
Difficulty: Medium
Learning Objective: 6
Topic: Outliers & Influential Observations 11511 Chapter 01  An Introduction to Business Statistics 91. In a multiple regression model with 4 independent variables and 25 observations, an
observation's actual y value is 128.2, and the predicted value of the dependent variable based
on the multiple regression equation is equal to 114.7. The computer output also shows that
MSE is equal to 144 and the leverage value is 0.19. Calculate the studentized residual for this
observation.
1.25 AACSB: Analytical Skills
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Outliers & Influential Observations 92. In a multiple regression model with 4 independent variables and 25 observations, an
observation's actual y value is 128.2, and the predicted value of the dependent variable based
on the multiple regression equation is equal to 114.7. The computer output also shows that
MSE is equal to 144 and the leverage value is 0.19. Calculate the deleted residual for this
observation.
16.6667 AACSB: Analytical Skills
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Outliers & Influential Observations 11512 Chapter 01  An Introduction to Business Statistics 93. In a multiple regression model with 4 independent variables and 25 observations, an
observation's actual y value is 128.2, and the predicted value of the dependent variable based
on the multiple regression equation is equal to 114.7. The computer output also shows that
MSE is equal to 144 and the leverage value is 0.19. Calculate the studentized deleted residual
for this observation.
1.269 AACSB: Analytical Skills
Bloom's: Application
Difficulty: Hard
Learning Objective: 6
Topic: Outliers & Influential Observations 94. In a multiple regression model with 4 independent variables and 25 observations, an
observation's actual y value is 128.2, and the predicted value of the dependent variable based
on...
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 Winter '14

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