7.0 Introduction

A student takes a ten-question, true-false quiz. Because the student had such a busy schedule, he or she could not study and guess randomly at each answer.  What is the probability of the student passing the test with at least a 70%?

Small companies might be interested in the number of long-distance phone calls their employees make during the peak time of the day.  Suppose the average is 20 calls.  What is the probability that the employees make more than 20 long-distance phone calls during the peak time?

These two examples illustrate two different types of probability problems involving discrete random variables.  Recall that discrete data are data that you can count.  A random variable describes the outcomes of a statistical experiment in words.  The values of a random variable can vary with each repetition of an experiment.

Random Variables

Upper case letters such as [latex]X[/latex] or [latex]Y[/latex] denote a random variable.  Lowercase letters like [latex]x[/latex] or [latex]y[/latex] denote the value of a random variable. If [latex]X[/latex] is a random variable, then [latex]X[/latex] is written in words, and [latex]x[/latex] is given as a number.

For example, let [latex]X[/latex] be the number of heads you get when you toss three fair coins.  The sample space for the toss of three fair coins is [latex]TTT, THH, HTH, HHT, HTT, THT, TTH, HHH[/latex]. Then, [latex]x = 0, 1, 2, 3[/latex]. [latex]X[/latex] is in words and [latex]x[/latex] is a number.  Notice that for this example, the [latex]x[/latex] values are countable outcomes.  Because you can count the possible values that [latex]X[/latex] can take on, and the outcomes are random (the [latex]x[/latex] values are [latex]0, 1, 2, 3[/latex]), [latex]X[/latex] is a discrete random variable.

A random variable describes a characteristic of interest in a population being studied.  Common notation for variables are upper case Latin letters [latex]X[/latex], [latex]Y[/latex], [latex]Z[/latex],… and common notation for a specific value from the domain (set of all possible values of a variable) are lower case Latin letters [latex]x, y,[/latex] and [latex]z[/latex].  For example, if [latex]X[/latex] is the number of children in a family, then [latex]x[/latex] represents a specific integer [latex]0, 1, 2, 3,....[/latex].  Variables in statistics differ from variables in intermediate algebra in the two following ways:

• The domain of the random variable is not necessarily a numerical set.  The domain may be expressed in words.  For example, if [latex]X[/latex] is hair colour, then the domain is {black, blond, gray, green, orange}.
• We can tell what specific value [latex]x[/latex] the random variable [latex]X[/latex] takes only after performing the experiment.

Attribution

“4.1 Introduction to Discrete Random Variables” from Introduction to Statistics by Valerie Watts is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.