Discrete Random Variables: Functions and Distributions

This lecture covers the definition of probability mass function for discrete random variables, including key properties such as non-negativity and total probability. It also introduces the binomial random variable and its mass function, along with the concepts of geometric and negative binomial distributions. The lecture further explores alternative forms of negative binomial distribution and discusses uniform, hypergeometric, and Poisson distributions. The importance of expectation in discrete random variables is highlighted, along with examples of calculating expectations for different distributions.