Advanced introduction to basic, non-measure theoretic probability covering topics in more depth and with more rigor than MATH 730. Topics include random variables with discrete and continuous distributions. Independence, joint distributions, conditional distributions, generating functions, Bayes' formula, and Markov chains. Rigorous arguments are presented for the law of large numbers, central limit theorem, and Poisson limit theorems. An assignment will ask the student to relate this course to their research.