A statistics professor wanted to develop a model to predict hovw long individual

Question

A statistics professor wanted to develop a model to predict hovw long individuals will live. After consulting a number of medical doctors, she collected the age at death (v), the average number of hours of exercise per week (x), the cholesterol level (x), and the number of points that the individual's blood pressure exceeded the recommended value (x. 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 + 1.79:0 0.02 1x.0 0.06 lx. 118 ANALYSIS OF VARIANCE otal a. Is there enough evidence at the 1% significance level to infer (or conclude) that the model is valid for predicting length of life? b. Calculate the coefficient of determination and interpret it. C. Is there enough evidence at the 10% significance level to infer (or conclude) that the average number of hours of exercise per week and the age at death are linearly related? d. Calculate the standard error of the estimate. What does this statistic tell you about the model?

Explanation / Answer

a) p-value of model is 0.04723 > 0.01

hence the model is not significant at 1 %

b) R^2 = 606/41066 = 0.14546

c) x1

T = 1.79 / 0.011 = 162.72 >> 2

hence significant

d)

standard error = sqrt(MSE) = 98.9

df SS MS F Significance F Regression 3 606 202 2.042696629 0.047237945 Residual 36 3560 98.88888889 Total 39 4166

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