Continuous random variables have many applications. Baseball batting averages, IQ scores, the length of time a long distance telephone call lasts, the amount of money a person carries, the length of time a computer chip lasts, rates of return from an investment, and SAT scores are just a few. The field of reliability depends on a variety of continuous random variables, as do all areas of risk analysis.

### Note

The values of discrete and continuous random variables can be ambiguous. For example, if *X* is equal to the number of miles (to the nearest mile) you drive to work, then *X* is a discrete random variable. You count the miles. If *X* is the distance you drive to work, then you measure values of *X* and *X* is a continuous random variable. For a second example, if *X* is equal to the number of books in a backpack, then *X* is a discrete random variable. If *X* is the weight of a book, then *X* is a continuous random variable because weights are measured. How the random variable is defined is very important.