Question 1

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below.
THE REGRESSION EQUATION IS:  
= 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0
  
S = 9.47 R-Sq = 22.5%
ANALYSIS OF VARIANCE
 
-Is there sufficient evidence at the 5% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value and the age at death show a negative linear relationship?

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Question 2

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: The computer output for the multiple regression model,y = βS1U1B10S1U1B0 + βS1U1B11S1U1B0XS1U1B11S1U1B0 + βS1U1B12S1U1B0XS1U1B12S1U1B0 + ε is shown below.However,because of a printer malfunction some of the results are not shown.These are identified by asterisks. S = * R-Sq = * ANALYSIS OF VARIANCE -If you want to test H₀ : β₁ = β₂ = 0 against H₁ : At least one β_j ≠ 0,(j = 1,2),what is the test statistic? What is your conclusion at the 5% level?

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Question 3

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below. THE REGRESSION EQUATION IS: = 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0 S = 9.47 R-Sq = 22.5% ANALYSIS OF VARIANCE -Interpret the coefficient b₁.

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Question 4

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below.
THE REGRESSION EQUATION IS:  
= 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0
  
S = 9.47 R-Sq = 22.5%
ANALYSIS OF VARIANCE
 
-Is there enough evidence at the 10% significance level to infer that the model is useful in predicting how long an individual will live?

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Question 5

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
The computer output for the multiple regression model,y = βS1U1B10S1U1B0 + βS1U1B11S1U1B0XS1U1B11S1U1B0 + βS1U1B12S1U1B0XS1U1B12S1U1B0 + ε is shown below.However,because of a printer malfunction some of the results are not shown.These are identified by asterisks.
  
S = * R-Sq = *
ANALYSIS OF VARIANCE
 
-Calculate the mean square for regression.

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Question 6

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below.
THE REGRESSION EQUATION IS:  
= 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0
  
S = 9.47 R-Sq = 22.5%
ANALYSIS OF VARIANCE
 
-What is the coefficient of determination? What does this statistic tell you?

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Question 7

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below. THE REGRESSION EQUATION IS: = 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0 S = 9.47 R-Sq = 22.5% ANALYSIS OF VARIANCE -Interpret the coefficient b₂.

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Question 8

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below.
THE REGRESSION EQUATION IS:  
= 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0
  
S = 9.47 R-Sq = 22.5%
ANALYSIS OF VARIANCE
 
-Is there enough evidence at the 1% significance level to infer that the average number of hours of exercise per week and the age at death are linearly related?

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Question 9

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below. THE REGRESSION EQUATION IS: = 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0 S = 9.47 R-Sq = 22.5% ANALYSIS OF VARIANCE -Interpret the coefficient b₃.

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Question 10

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
The computer output for the multiple regression model,y = βS1U1B10S1U1B0 + βS1U1B11S1U1B0XS1U1B11S1U1B0 + βS1U1B12S1U1B0XS1U1B12S1U1B0 + ε is shown below.However,because of a printer malfunction some of the results are not shown.These are identified by asterisks.
  
S = * R-Sq = *
ANALYSIS OF VARIANCE
 
-Calculate the unbiased estimate of error variance.

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Question 11

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
The computer output for the multiple regression model,y = βS1U1B10S1U1B0 + βS1U1B11S1U1B0XS1U1B11S1U1B0 + βS1U1B12S1U1B0XS1U1B12S1U1B0 + ε is shown below.However,because of a printer malfunction some of the results are not shown.These are identified by asterisks.
  
S = * R-Sq = *
ANALYSIS OF VARIANCE
 
-Calculate the standard error of the estimate.

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Question 12

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION:
An actuary wanted to develop a model to predict how long individuals will live.After consulting a number of physicians,she collected the age at death (y),the average number of hours of exercise per week (xS1U1B11S1U1B0),the cholesterol level (xS1U1B12S1U1B0),and the number of points that the individual's blood pressure exceeded the recommended value (xS1U1B13S1U1B0).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below.
THE REGRESSION EQUATION IS:  
= 55.8 + 1.79xS1U1B11S1U1B0 - 0.021xS1U1B12S1U1B0 - 0.016xS1U1B13S1U1B0
  
S = 9.47 R-Sq = 22.5%
ANALYSIS OF VARIANCE
 
-Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death show a negative linear relationship?

Accepted Answer

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Quiz 12: Multiple Regression