ABSTRACT
This chapter describes a famous “matching” probability problem i.e. the hat check problem. It discusses the concepts of random variable and probability distribution by using the coin flipping problem. In general, suppose X is a discrete random variable. This type of random variable only assigns probability to a discrete set of values. A probability distribution is a listing of the values of X together with the associated values of the probability mass function. One graphically displays this probability distribution with a bar graph. The chapter shows that a binomial probability model applies to many different random phenomena in the real world. It discusses probability computations for the binomial and the closely related negative binomial models and illustrates the usefulness of these models in representing the variation in real-life experiments.
