This course builds a rigorous foundation of probability. Topics covered include: basic concepts of probability theory and statistics, counting, axioms of probability, independence, Bayes rule, ...

On this page you will find a listing of (selected) graduate course descriptions. Also see course listings for current semester. Office of the Registrar: Register for Classes Prerequisite: MTH 142 or ...

Introduction to probability theory and its applications. Axioms of probability, distributions, discrete and continuous random variables, conditional and joint distributions, correlation, limit laws, ...

The course provides a precise and accurate treatment of probability, distribution theory and statistical inference. As such there will be a strong emphasis on mathematical statistics as important ...

Descriptive statistics, basic concepts of probability and sampling with the aim of introducing fundamental notions and techniques of statistical inference. Prerequisite: Math 10 or a score of 51 or ...