A function that maps values of a discrete random variable to a real number is called a probability mass function (PMF).

The PMF gives the probability that a discrete random variable is exactly equal to a specific value. In formal terms, if $X$ is a discrete random variable, then the PMF $P(X = x)$ gives the probability that $X$ takes the value $x$.

Would you like more details or have any questions?

Here are 5 related questions for further exploration:

1. What is the difference between a probability mass function and a probability density function?
2. How do you calculate the expected value of a discrete random variable?
3. What is the cumulative distribution function (CDF) for a discrete random variable?
4. How does the law of large numbers relate to discrete random variables?
5. What is the significance of the variance for a discrete random variable?

Tip: When working with discrete random variables, ensure that the sum of all probabilities in the PMF equals 1.