This chapter presents the fundamental concepts of probability and probability distributions. Probability values can be obtained objectively or subjectively. A single probability value must be between 0 and 1, and the sum of all probability values for all possible outcomes must be equal to 1. In addition, probability values and events can have a number of properties. These properties include mutually exclusive, collectively exhaustive, statistically independent, and statistically dependent events. Rules for computing probability values depend on these fundamental properties. It is also possible to revise probability values when new information becomes available. This can be done using Bayes’ Theorem.

We also covered the topics of random variables, discrete probability distributions (such as Poisson and binomial), and continuous probability distributions (such as normal, F, and exponential). A probability distribution is any statement of a probability function having a set of collectively exhaustive and mutually exclusive events. All probability distributions follow the basic probability rules mentioned previously.

The topics presented here will be very important in many of the chapters to come. Basic probability concepts and distributions are used for decision theory, inventory control, Markov analysis, project management, simulation, and statistical quality control.