OMIS 2010 Chapter Notes - Chapter 08: Standard Normal Deviate, Random Variable, Exponential Distribution

• School: York University
• Department: Operations Management and Information System
• Course: OMIS 2010
• Professor: Alan Marshall

Document Summary

This chapter continued our discussion of probability distributions. It began by describing continuous probability distributions in general, and then took a detailed look at the normal distribution, which is the most important specific continuous distribution. This section introduced the notion of a continuous random variable, which differs from a discrete random variable both in the type of numerical events of interest and the type of function used to find probabilities. Hence, for a continuous random variable x, it is only meaningful to talk about the probability that x will assume a value within a particular interval. Such a probability is found using the probability density function, f(x), associated with x. The probability that x will take a value in the interval a < x < b is given by the area under the graph of f(x) between the values a and b.