Offered through the University of Maryland

STAT410: Probability Theory is a University of Maryland course that gives a proof-based introduction to the formulation and manipulation of probability models, leading up to a rigorous proof of the law of large numbers and the central limit theorem. The emphasis is on concepts: sets and combinatorics allow a precise mathematical formulation of probability models, multivariable calculus supplies machinery for changing variables and calculating probabilities and average values relating to vectors of real-valued random variables, and limit theorems allow event-occurrences which are individually unpredictable to become predictable in the aggregate.

The subject is taught to University of Maryland upper-level undergraduate students. Details for the class are here.

← CMSC451: Design and Analysis of Algorithms | Class Archive | MATH405: Linear Algebra →


I’m Kevin Chen, and this is my personal website. I am a rising final-year student in the CS department at the University of Maryland. ¶ My research interests are in machine learning and theoretical computer science. I enjoy reading, filmmaking, tennis and helping out with Bitcamp.


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