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Life insurance companies are keenly interested in predicting how long their cust

ID: 3320664 • Letter: L

Question

Life insurance companies are keenly interested in predicting how long their customers will live because their premiums and profitability depend on such numbers. An actuary for one insurance company gathered data from 100 recently deceased male customers. He recorded the age at death of customer plus the ages at death of his mother and father, the mean ages at death of his grandmother and mean age of death of grandfather.

Longevity            mother                 father                   gmother              gfather

80                           85                           78                           72                           71

73                           88                           63                           76                           66

70                           66                           75                           67                           57

72                           72                           67                           68                           55

79                           88                           73                           64                           73

83                           90                           72                           74                           62

70                           67                           65                           70                           59

i) You think that it would be a better regression model if only two variables, the ages of the customer’s mother and father, were used to predict longevity.

Perform a multiple regression of y on x based upon the two variables stated in the problem above.

The least squares regression equation is:

                a.            y hat = 6.48 + 0.47x1 + 0.43x2

                b.            y = 13.52 + 0.50x1 + 3.395x2

                c.             y hat = 3.24 + 0.45x1 + 0.44x2 + 0.01x3

                d.            none of the above

ii) You think that it would be a better regression model if only two variables, the ages of the customer’s mother and father, were used to predict longevity.

Perform a multiple regression of y on x based upon the two variables stated in the problem above.

Using the appropriate hypothesis tests, which independent variables are indicated as being linearly related to the dependent variable, as shown by results utilizing the appropriate two-tailed hypothesis tests?

                a.            the variables “mother” and “father” may be linearly related to the dependent variable, holding other independent variables constant.

                b.            the variable “father”, is the only variable that may be linearly related to the dependent variable, holding other independent variables constant.

                c.             the variable “mother” is the only variable that may be linearly related to the dependent variable, holding other independent variables constant.

                d.            none of the independent variables are linearly related to the dependent variable.

Explanation / Answer

We use Minitab to solve this question,

Regression Analysis: Longevity versus mother, father

Analysis of Variance

Source DF Adj SS Adj MS F-Value P-Value
Regression 2 143.47 71.735 11.98 0.020
mother 1 99.24 99.239 16.57 0.015
father 1 27.18 27.184 4.54 0.100
Error 4 23.96 5.990
Total 6 167.43


Coefficients

Term Coef SE Coef T-Value P-Value VIF
Constant 17.3 14.0 1.24 0.284
mother 0.3858 0.0948 4.07 0.015 1.02
father 0.388 0.182 2.13 0.100 1.02


Regression Equation

Longevity = 17.3 + 0.3858 mother + 0.388 father

a multiple regression of y on x based upon the two variables stated in the problem above.

The correct option for least squares regression equation .

None of the above.

we think that it would be a better regression model if only two variables, the ages of the customer’s mother and father, were used to predict longevity the estimated regression is,

Longevity = 17.3 + 0.3858 mother + 0.388 father

Using the appropriate hypothesis tests, which independent variables are indicated as being linearly related to the dependent variable,

a.            the variables “mother” and “father” may be linearly related to the dependent variable, holding other independent variables constant.

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