6.436J | Fall 2018 | Graduate
Fundamentals of Probability
Course Description
This is a course on the fundamentals of probability geared towards first or second-year graduate students who are interested in a rigorous development of the subject. The course covers sample space, random variables, expectations, transforms, Bernoulli and Poisson processes, finite Markov chains, and limit theorems. …
This is a course on the fundamentals of probability geared towards first or second-year graduate students who are interested in a rigorous development of the subject. The course covers sample space, random variables, expectations, transforms, Bernoulli and Poisson processes, finite Markov chains, and limit theorems. There is also a number of additional topics such as: language, terminology, and key results from measure theory; interchange of limits and expectations; multivariate Gaussian distributions; and deeper understanding of conditional distributions and expectations.
Learning Resource Types
assignment_turned_in Problem Sets with Solutions
grading Exams
notes Lecture Notes
Two red dice on a surface.
The rolling of dice is one of the most classic examples of probability. Photo by Jonathan Petersson on Unsplash.