CHAPTER 3

Random Variables, Distributions, and Density Functions

At the end of the last chapter, we introduced the concept of a random variable and gave several examples of common discrete random variables. These random variables were described by their probability mass functions. While this description works fine for discrete random variables, it is inadequate to describe random variables that take on a continuum of values. We will illustrate this through an example shortly. In this chapter, we introduce the cumulative distribution function (CDF) as an alternative description of random variables that is appropriate for describing continuous as well as discrete random variables. A related function, the probability density function (PDF), is ...

Get Probability and Random Processes, 2nd Edition now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.