STAT 400 Study Guide - Final Guide: Poisson Distribution, Poisson Point Process, Binomial Distribution
13 Dec 2018
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Stat 400, section 3. 6a poisson & 3. 5c geometric random variables notes prepared by tim pilachowski. Poisson distributions model (some) discrete random variables, usually x = 0, 1, 2, Typically, a poisson random variable is a count of the number of events that occur in a certain time interval or spatial area. For example, the number of cars passing a fixed point in a 5 minute interval, or the number of calls received by a switchboard during a given period of time. A discrete random variable x is said to follow a poisson distribution with parameter , if it has probability distribution. The poisson distribution has expected value e(x) = and v(x) = . Example a: between 1900 through 2000, 168 hurricanes made landfall in the united states at an average rate of 1. 66 per year. Find the probabilities that a) 3, b) fewer than 3, and c) more than 3 hurricanes will reach the u. s. during a particular year.
