Statisticians have identified several classes of function suitable for explaining the probability distribution of both discrete and continuous variables. These classes of functions can be considered to be probability models for explaining observed data, and provide the necessary link for inferring population properties from sample data. The theoretical (population) probability distribution of a random variable is determined by a small set of population parameters that can be estimated using the sample data. This chapter will present definitions and examples of probability distributions for both discrete and continuous variables.