AM1.234

# AM1.234 - Introduction to Actuarial Mathematics Chapter 1...

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Introduction to Actuarial Mathematics Chapter 1 – The Life Table Introduction (section 1.1) American Benjamin Franklin once said: “There is nothing certain in life except death and taxes” However, it is equally true that for any individual, there is nothing so uncertain as the time of one’s death

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But, it is known, with relative certainty, that out of a large group of individuals chosen at random, some will die within a certain period of time However, we do not know which actual individuals in the group will die
We can estimate the probability of death or survival We can use large group data, along with probability theory to estimate the probability that an individual will die (or survive) within a given period of time when we combine the probability of a future event occurring with an interest rate, we enter the world of actuarial science

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We will be dealing with financial products such as life annuities and life insurance The structure of these products depends on 3 key elements: 1. The probability of death/survival of a given individual over a given period of time 2. The interest rate that can be earned on invested money 3. The rate of expense incurred in the sale and maintenance of a life annuity or life insurance product
Probability plays an important role in the study of actuarial mathematics it is used in the construction of life tables , which are tables of the probability of dying/surviving over 1 year periods for individuals of various ages life tables are also used to calculate how much an insurance company can charge its customers when selling a life annuity or life insurance product

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Probability (section 1.2) You can read section 8.1 of the Zima – Brown−Kopp textbook for more background Classical Definition of Probability Suppose you have an event that is either a success or failure suppose this event can be successful in h -ways and fail in f -ways, all of which are equally likely Then, p = probability of success = q = probability of failure =
We see that, p + q = This definition of probability can be used

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## This note was uploaded on 04/14/2010 for the course ACSCI 2053 taught by Professor Kopp during the Spring '09 term at UWO.

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AM1.234 - Introduction to Actuarial Mathematics Chapter 1...

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