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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 10% significance level to infer that the model is useful in predicting how long an individual will live?
= 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 10% significance level to infer that the model is useful in predicting how long an individual will live?
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 10% significance level to infer that the model is useful in predicting how long an individual will live?
-Is there enough evidence at the 10% significance level to infer that the model is useful in predicting how long an individual will live?


Definitions:

Floor Price

The minimum price set by regulation, often by the government, below which a commodity cannot legally be sold in the market.

Market Supply

The total amount of a specific good or service that is available to consumers in a market at a given time and price.

Equilibrium Price

Equilibrium price is the price at which the quantity of a good demanded by consumers equals the quantity supplied by producers, leading to market stability.

Consumer Surplus

The difference in the total expected payment consumers are ready to make for a good or service and their actual expenditures.

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