In this chapter we began our study of random variables. We learned that a random variable represents an uncertain numerical outcome. We also learned that a random variable whose values can be listed is called a discrete random variable, while the values of a continuous random variable correspond to one or more intervals on the real number line. We saw that a probability distribution of a discrete random variable is a table, graph, or formula that gives the probability associated with each of the random variable's possible values. We also discussed several descriptive measures of a discrete random variable—its mean (or expected value), its variance, and its standard deviation. We concluded this chapter by studying two important, commonly used discrete probability distributions—the binomial distribution and the Poisson distribution—and we demonstrated how these distributions can be used to make statistical inferences.