Mortality

Mortality Objective: Evaluating data and drawing conclusions about life expectancy. Motivation: Insurance agents know that the premium or cost of an insurance policy is based on the likelihood of a claim being filed. In the case of life insurance, the insurance company is Well... making a bet that the client will survive. The you won client is betting that they will not, in which case a cash value will be forwarded to his or her the bet. beneficiary. The fairness of the amount of the premium and the value of the policy are all based on mathematical statistics gathered from Norah's large samples of individuals in what is called Agency RIP mortality table. One of the earliest mortality tables was compiled by Edmund Halley, for whom the Comet is named, in 1693. The data in mortality tables are used to make predictions about the life spans of people who are still alive. The Activity According to mortality table the life expectancy for the general population is 80, otherwise u = 80. Question: 1. What are your feelings about how the life expectancy locally (Bay Area) compares with the national average. Explain. Follow up question: 2. How do you think the above claim could be substantiated? 3. Collect and list your data, use internet if you must, making sure that the gender is identified in your sample: (Obviously more data you collect, your result will be better. Make sure your data is not redundant. You should have at least 40 data values.)4. For your data nd the following: 3? = n = m: 5. According to CLT What is (If: '? (Assume that Sx = 0'.) 6. Use to scale the graph. 7. How many standard deviations (oi) does your sample average falls from the hypothesized mean (u) of 80? 8. Mark your sample average, , on the graph above. Is your sample outcome consistent with the national average or does it support your claim? Explain. 9. Would collecting all the data gathered by the class into a large pool enhance or diminish the quality of the data? Explain