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.
Course Info
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grading
Exams
notes
Lecture Notes
assignment
Problem Sets
![Two red dice on a surface.](/courses/6-436j-fundamentals-of-probability-fall-2018/9333adb234a206385d9ddd1de8bae72e_6-436F18.jpg)
The rolling of dice is one of the most classic examples of probability. Photo by Jonathan Petersson on Unsplash.