Probability Theory

Instructor: Anand Deo

Course overview

This introductory graduate course is designed to equip participants with a background in probability theory. The course will focus on understanding various probabilistic and statistical tools used in applications broadly related to management sciences, as well as their limitations. Topics covered will include discrete and continuous random variables, univariate and multivariate probability theory, conditional expectations and probabilistic limit theorems. The course will also provide an introduction to useful modelling and computational tools such as Markov Chains, Poisson Processes and Monte-Carlo methods, each of which shall be presented as applications of the developed theory.

Textbooks

1. A First Course in Probability: Sheldon Ross

2. Introduction to Probability: Bertsekas and Tsitsikilis

3. Introduction to Probability Models: Sheldon Ross

4. Material as referenced in lecture slides

Code implementations used in this course are available here