EAS 502LEC - Introduction to Probability Theory for Data Science

This course provides basic background on probability theory at a beginning graduate level. Topics include introductory probability concepts, discrete and continuous random variables and probability distributions, joint and conditional probability distributions, Bayes theorem and its applications, random sampling and data description, point estimation of parameters, discrete and continuous transforms and random incidence. If time permits the course introduces elementary stochastic processes including Bernoulli and Poisson processes.

Credits: 3