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4 DISCRETE PROBABILITY DISTRIBUTIONS. Objectives. After studying this chapter you should. understand what is meant by a discrete probability distribution; be able to find the mean and variance of a distribution; be able to use the uniform distribution. 4.0 Introduction. The definition. ' X = the total when two standard dice are rolled'
Discrete probability distributions. The binomial distribution. The Poisson distribution. The hypergeometric distribution. Learning. outcomes. In this workbook you will learn what a discrete random variable is. You will find how to calculate the expectation and variance of a discrete random variable.
Discrete Probability Worksheet 1. If you are dealt a hand of ve cards from a deck of 52, calculate the probability of each of the following events.
A discrete probability distribution function has two characteristics: Each probability is between zero and one, inclusive. The sum of the probabilities is one. Example 4.1. A child psychologist is interested in the number of times a newborn baby's crying wakes its mother after midnight.
Chapter 11 – Discrete probability distributions Solutions to Exercise 11A 1 a Not a prob. function, P Pr , 1 b Not a prob. function, P Pr , 1 c Prob. function: P Pr = 1 and 0 p 1 for all p d Not a prob. function, P Pr , 1 e Not a prob. function because p(3) < 0 2 a Pr(X = 2) b Pr(X > 2) c Pr(X 2) d Pr(X < 2) e Pr(X 2) f Pr(X > 2)
Discrete Probability Worksheet 3 Solutions. 1. Suppose you ip two fair coins. Let A be the event that the rst coin is heads, B the event that the second coin is heads and C the event that both coins show the same face. Are A and. B independent? A and C? B and C? How about A, B, and C?
Use the Poisson distribution to find the probability that the company makes a profit from the 1300 policies. Use the binomial distribution to find the probability that the company makes a profit from the 1300 policies, then compare the result to the result found in part (b).
