Any characteristic that can be measured or categorized is called a variable. If a variable can assume a number of different values such that any particular outcome is determined by chance, it is a random variable. We have already looked at a number of different random variables in previous chapters, although we did not use this term. In Chapter 2, for instance, the serum cholesterol level of a 25- to 34-year-old male in the United States is a random variable; in Chapter 3, forced expiratory volume in 1 second for an adolescent suffering from asthma is another. Random variables are typically represented by uppercase letters such as X, Y, and Z. A discrete random variable can assume only a finite or countable number of outcomes. One example is marital status: an individual can be single, married, divorced, or widowed. Another example would be the number of ear infections an infant develops during his or her first year of life. A continuous random variable, such as weight or height, can take on any value within a specified interval or continuum.