As a life insurance company, it\'s important to be able to predict when you\'ll

Question

As a life insurance company, it's important to be able to predict when you'll be paying out, and how long you can expect to collect premiums. Predicting how long people will live allows you to do both of these things. Below is the SPSS output from the age of death of insured people, their weight (Body Mass Index) and whether they were a smoker (Smoker = 1) or not (Smoker = 0). a. Dependent Variable: Life Expectancy a) What type of analysis was done to get these results? b) Write the regression equation. c) What does the intercept mean in this case? d) What type of variable is Smoker? e) Explain what the smoker slope means in real world terms. f) Do smokers live a different length than non-smokers of the same weight? Show your work. Alpha = 0.05

Explanation / Answer

a) multiple regression

b) y^ = 97.809 -0.692 * BMI -6.746*D

where D is dummy for smoker

c) intercept is 97.809 means when BMI is 0 and the person is not 0 , then age of death will be 97.809

d)Smoker is dummy variable

e) slope of smoker means that average age of death for smoker is 6.746 years less than those who don't smoke

f) p-value for smoker is 0.023 < 0.05

hence we reject the null , and we conclude that there is difference in length between two

Please don't forget to rate positively if you found this response helpful.
Feel free to comment on the answer if some part is not clear or you would like to be elaborated upon.
Thanks and have a good day!

Related Questions

Navigate

• Browse (All)
• Browse A
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.