Question 1

Life Expectancy 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0 S = 9.47 R−Sq = 22.5% ANALYSIS OF VARIANCE -{Life Expectancy Narrative} Interpret the coefficient b₁.

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 An actuary wanted to...

Question 2

Student's Final Grade 
A statistics professor investigated some of the factors that affect an individual student's final grade in her course.She proposed the multiple regression model  ,where y is the final grade (out of 100 points),xS1U1B11S1U1B0 is the number of lectures skipped,xS1U1B12S1U1B0 is the number of late assignments,and xS1U1B13S1U1B0 is the midterm exam score (out of 100).The professor recorded the data for 50 randomly selected students.The computer output is shown below. THE REGRESSION EQUATION IS  ​  ​ ​ S = 13.74 R−Sq = 30.0% ​ ANALYSIS OF VARIANCE  ​ ​
-{Student's Final Grade Narrative} What is the coefficient of determination? What does this statistic tell you?

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A statistics professor investigated...

Question 3

Life Expectancy
 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0  ​ S = 9.47 ​ R−Sq = 22.5% ANALYSIS OF VARIANCE  ​ ​
-{Life Expectancy Narrative} What is the adjusted coefficient of determination in this situation? What does this statistic tell you?

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 An actuary wanted to...

Question 4

The computer output for the multiple regression model  is shown below.However,because of a printer malfunction some of the results are not shown.These are indicated by the boldface letters a to i.Fill in the missing results (up to three decimal places).  S = d
R−Sq = e
ANALYSIS OF VARIANCE

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The answer of The computer output for the multiple regression...

Question 5

Life Expectancy
 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0  ​ S = 9.47 ​ R−Sq = 22.5% ANALYSIS OF VARIANCE  ​ ​
-{Life Expectancy Narrative} 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 are negatively linearly related?

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 An actuary wanted to...

Question 6

We test an individual coefficient in a multiple regression model using a(n)_________ test.

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Question 7

Consider the following statistics of a multiple regression model: Total variation in y = 1000,SSE = 300,n = 50,and k = 4.
a.Determine the standard error of estimate.
b.Determine the coefficient of determination.
c.Determine the F-statistic.

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The answer of Consider the following statistics of a multiple...

Question 8

Life Expectancy
 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0  ​ S = 9.47 ​ R−Sq = 22.5% ANALYSIS OF VARIANCE  ​ ​
-{Life Expectancy Narrative} What is the coefficient of determination? What does this statistic tell you?

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The answer of  Life Expectancy
 An actuary wanted to...

Question 9

Some of the requirements for the error variable in a multiple regression model are that the probability distribution is ____________________ with a mean of ____________________.

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Question 10

Life Expectancy
 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0  ​ S = 9.47 ​ R−Sq = 22.5% ANALYSIS OF VARIANCE  ​ ​
-{Life Expectancy Narrative} Is there enough evidence at the 5% significance level to infer that the cholesterol level and the age at death are negatively linearly related?

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The answer of  Life Expectancy
 An actuary wanted to...

Question 11

Life Expectancy 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0 S = 9.47 R−Sq = 22.5% ANALYSIS OF VARIANCE -{Life Expectancy Narrative} Interpret the coefficient b₃.

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 An actuary wanted to...

Question 12

Consider the following statistics of a multiple regression model: n = 25,k = 5,b₁ = −6.31,and sε = 2.98.Can we conclude at the 1% significance level that x₁ and y are linearly related?

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The answer of Consider the following statistics of a multiple...

Question 13

Life Expectancy
 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0  ​ S = 9.47 ​ R−Sq = 22.5% ANALYSIS OF VARIANCE  ​ ​
-{Life Expectancy Narrative} 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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The answer of  Life Expectancy
 An actuary wanted to...

Question 14

The coefficient of determination ____________________ for degrees of freedom takes into account the sample size and the number of independent variables when assessing model fit.

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Question 15

When there is more than one independent variable in a regression model,we refer to the graphical depiction of the equation as a(n)____________________ rather than as a straight line.

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Question 16

Some of the requirements for the error variable in a multiple regression model are that the standard deviation is a(n)____________________ and the errors are ____________________.

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The answer of Some of the requirements for the error...

Question 17

Life Expectancy
 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0  ​ S = 9.47 ​ R−Sq = 22.5% ANALYSIS OF VARIANCE  ​ ​
-{Life Expectancy Narrative} Is there enough evidence at the 5% significance level to infer that the model is useful in predicting length of life?

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 An actuary wanted to...

Question 18

A(n)____________________ value of the F-test statistic indicates that the multiple regression model is valid.

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Question 19

The total variation in y is equal to SSR + ____________________.

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Question 20

Life Expectancy 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 y = 55.8 + 1.79xS1U1B11S1U1B0− 0.021xS1U1B12S1U1B0− 0.061xS1U1B13S1U1B0 S = 9.47 R−Sq = 22.5% ANALYSIS OF VARIANCE -{Life Expectancy Narrative} Interpret the coefficient b₂.

Accepted Answer

The answer of  Life Expectancy
 An actuary wanted to...

Quiz 17: Multiple Regression

The computer output for the multiple regression model is shown below.However,because of a printer malfunction some of the results are not shown.These are indicated by the boldface letters a to i.Fill in the missing results (up to three decimal places). S = d R−Sq = e ANALYSIS OF VARIANCE

We test an individual coefficient in a multiple regression model using a(n)_________ test.

Consider the following statistics of a multiple regression model: Total variation in y = 1000,SSE = 300,n = 50,and k = 4. a.Determine the standard error of estimate. b.Determine the coefficient of determination. c.Determine the F-statistic.

Some of the requirements for the error variable in a multiple regression model are that the probability distribution is with a mean of .

Consider the following statistics of a multiple regression model: n = 25,k = 5,b₁ = −6.31,and sε = 2.98.Can we conclude at the 1% significance level that x₁ and y are linearly related?

The coefficient of determination ____________________ for degrees of freedom takes into account the sample size and the number of independent variables when assessing model fit.

When there is more than one independent variable in a regression model,we refer to the graphical depiction of the equation as a(n)____________________ rather than as a straight line.

Some of the requirements for the error variable in a multiple regression model are that the standard deviation is a(n) and the errors are .

A(n)____________________ value of the F-test statistic indicates that the multiple regression model is valid.

The total variation in y is equal to SSR + ____________________.

Quiz 17: Multiple Regression

The computer output for the multiple regression model is shown below.However,because of a printer malfunction some of the results are not shown.These are indicated by the boldface letters a to i.Fill in the missing results (up to three decimal places). S = d R−Sq = e ANALYSIS OF VARIANCE

We test an individual coefficient in a multiple regression model using a(n)_________ test.

Consider the following statistics of a multiple regression model: Total variation in y = 1000,SSE = 300,n = 50,and k = 4. a.Determine the standard error of estimate. b.Determine the coefficient of determination. c.Determine the F-statistic.

Some of the requirements for the error variable in a multiple regression model are that the probability distribution is ____________________ with a mean of ____________________.

Consider the following statistics of a multiple regression model: n = 25,k = 5,b1 = −6.31,and sε = 2.98.Can we conclude at the 1% significance level that x1 and y are linearly related?

The coefficient of determination ____________________ for degrees of freedom takes into account the sample size and the number of independent variables when assessing model fit.

When there is more than one independent variable in a regression model,we refer to the graphical depiction of the equation as a(n)____________________ rather than as a straight line.

Some of the requirements for the error variable in a multiple regression model are that the standard deviation is a(n)____________________ and the errors are ____________________.

A(n)____________________ value of the F-test statistic indicates that the multiple regression model is valid.

The total variation in y is equal to SSR + ____________________.

Some of the requirements for the error variable in a multiple regression model are that the probability distribution is with a mean of .

Consider the following statistics of a multiple regression model: n = 25,k = 5,b₁ = −6.31,and sε = 2.98.Can we conclude at the 1% significance level that x₁ and y are linearly related?

Some of the requirements for the error variable in a multiple regression model are that the standard deviation is a(n) and the errors are .