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.
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