1. 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. (50 points) Predictor Coef StDev T Constant 55.8 11.8 X1 1.79 0.44 X2 -0.021 0.011 X3 -0.016 0.014 S = 9.47 R-sq = 22.5% ANALYSIS OF VARIANCE Source of Variation df SS MS F Regression 3 936 312 3.477 Error 36 3230 89.722 Total 39 4166 a. Determine the regression equation (estimated linear model equation or least squares equation). b. What is the standard error of estimate (estimated standard deviation of error)? Briefly describe how you interpret this statistic. c. What is the coefficient of determination? What does this statistic tell you? d. Interpret each of the coefficients. e. Test the validity of the model. f. Estimate the coefficient of the number of points that the individual's blood pressure exceeded the recommended value with 95 percent confidence. g. Is there enough evidence at the 1% significance level to infer that the number of points that the individual's blood pressure exceeded the recommended value is useful in predicting length of life