Life insurance companies are keenly interested in predicting how long their customers are likely to live, because this will determine their premiums and ultimately their profitability. An Australian life insurance company is interested in the relationship, if any, between the age at death of their male customers and that of the customer’s father. Data are collected on a random sample of 100 of their male customers who have recently died. The customer’s age at death was plotted against that of their father and a linear regression model applied. Relevant output is shown below. Say how you know from the output that there actually is a significant linear relationship between a male customer’s age at death and his father’s age at death. State the value of the coefficient of Father’s Age (Death) and interpret this value in the context of the problem at hand. State the value of the coefficient of determination in the model and interpret this value in the context of the situation.
Life insurance companies are keenly interested in predicting how long their customers are likely to live, because this will determine their premiums and ultimately their profitability. An Australian life insurance company is interested in the relationship, if any, between the age at death of their male customers and that of the customer’s father. Data are collected on a random sample of 100 of their male customers who have recently died. The customer’s age at death was plotted against that of their father and a linear regression model applied. Relevant output is shown below. Say how you know from the output that there actually is a significant linear relationship between a male customer’s age at death and his father’s age at death. State the value of the coefficient of Father’s Age (Death) and interpret this value in the context of the problem at hand. State the value of the coefficient of determination in the model and interpret this value in the context of the situation.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Life insurance companies are keenly interested in predicting how long their customers are
likely to live, because this will determine their premiums and ultimately their profitability.
An Australian life insurance company is interested in the relationship, if any, between the age
at death of their male customers and that of the customer’s father. Data are collected on a
random sample of 100 of their male customers who have recently died. The customer’s age at
death was plotted against that of their father and a linear regression model applied. Relevant
output is shown below.
Say how you know from the output that there actually is a significant linear relationship
between a male customer’s age at death and his father’s age at death.
State the value of the coefficient of Father’s Age (Death) and interpret this value in the
context of the problem at hand.
State the value of the coefficient of determination in the model and interpret this value in
the context of the situation.
Transcribed Image Text:Customer's Age (Death)
100
90
80
70
60
50
40
40
Customer's Age at Death V Father's Age
50
Father's Age (Death)
Customer's Age (Death)
60
70
Father's Age (Death)
80
0.664342737
90
Father's Age (Death) Customer's Age (Death)
1
100
Transcribed Image Text:SUMMARY OUTPUT
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression Statistics
Regression
Residual
Total
Intercept
Father's Age (Death)
0.664342737
0.441351272
0.435650775
3.852625943
100
af
SS
MS
1 1149.172787 1149.172787
98 1454.587213 14.84272666
99
2603.76
Coefficients
33.37737149
0.566273499 0.064356203 8.799050734
Standard Error t Stat
4.442512962 7.513173688
77.42329382
P-value
2.73096E-11
4.86735E-14
Significance F
4.86735E-14
Lower 95%
Upper 95% Lower 95.0% Upper 95.0%
24.56134911 42.19339388 24.56134911 42.1933938
0.69398629 0.438560708 0.6939862
0.438560708
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