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THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION

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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 (x1),the cholesterol level (x2),and the number of points that the individual's blood pressure exceeded the recommended value (x3).A random sample of 40 individuals was selected.The computer output of the multiple regression model is shown below.
THE REGRESSION EQUATION IS: 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 (x<sub>1</sub>),the cholesterol level (x<sub>2</sub>),and the number of points that the individual's blood pressure exceeded the recommended value (x<sub>3</sub>).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 + 1.79x<sub>1</sub> - 0.021x<sub>2</sub> - 0.016x<sub>3</sub> 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?
= 55.8 + 1.79x1 - 0.021x2 - 0.016x3
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 (x<sub>1</sub>),the cholesterol level (x<sub>2</sub>),and the number of points that the individual's blood pressure exceeded the recommended value (x<sub>3</sub>).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 + 1.79x<sub>1</sub> - 0.021x<sub>2</sub> - 0.016x<sub>3</sub> 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?
S = 9.47 R-Sq = 22.5%
ANALYSIS OF VARIANCE
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 (x<sub>1</sub>),the cholesterol level (x<sub>2</sub>),and the number of points that the individual's blood pressure exceeded the recommended value (x<sub>3</sub>).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 + 1.79x<sub>1</sub> - 0.021x<sub>2</sub> - 0.016x<sub>3</sub> 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?
-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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H0 : β1 = 0 against H1 : β1 ≠ 0
Rejection regi...

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