Whether an experiment yields qualitative or quantitative outcomes, methods of statistical analysis require that we focus on certain numerical aspects of the data (such as a sample proportion x/n, mean $$ \bar{x} $$, or standard deviation s). The concept of a random variable allows us to pass from the experimental outcomes themselves to a numerical function of the outcomes. There are two fundamentally different types of random variables---discrete random variables and continuous random variables. In this chapter, we examine the basic properties and discuss the most important examples of discrete variables. Chapter 4 focuses on continuous random variables.
CITATION STYLE
Devore, J. L., & Berk, K. N. (2012). Discrete Random Variables and Probability Distributions (pp. 96–157). https://doi.org/10.1007/978-1-4614-0391-3_3
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