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45 reject h0 aacsb analytical skills blooms

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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 by-pass 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 1-1509 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 1-1510 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 1-1511 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 1-1512 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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