Stochastic Processes
MATH 233
Spring 2027
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01
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This course provides a rigorous introduction to the theory of stochastic processes. Topics include a review of basic concepts of probability theory (probability spaces, random variables, expectation), Markov chains, Poisson processes, random walks, and Brownian motion. Students entering the course should have completed MATH231, and be comfortable with multivariable calculus and linear algebra. |
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| Credit: 1 |
Gen Ed Area Dept:
NSM MATH |
| Course Format: Lecture | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: MATH231 |
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Fulfills a Requirement for: (Applied Data Science Certificate)(Data Analysis Minor)(Mathematics) |
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