Stochastic Processes
MATH 233
Spring 2024
| Section:
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. In tandem, the workshop section taught by the Hazel Quantitative Analysis Center (QAC) will provide practical skills in R programming. These workshops are geared towards novices in programing and will detail ways to computationally tackle more complex, real-life stochastic processes. Students entering the course should have completed MATH231, and be comfortable with multivariable calculus and linear algebra. |
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| Credit: 1.5 |
Gen Ed Area Dept:
NSM MATH |
| Course Format: Lecture | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: MATH231 |
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Fulfills a Requirement for: (CADS)(DATA-MN)(MATH) |
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Past Enrollment Probability: 90% or above |
| SECTION 01 |
| Instructor(s): Oleinikov,Pavel V Li,Han Times: .M...F. 01:20PM-02:40PM; ...W... 01:20PM-02:40PM; Location: SCIE638; SCIE72; |
| Total Enrollment Limit: 24 | | SR major: 8 | JR major: 8 | | |
| Seats Available: 16 | GRAD: X | SR non-major: 1 | JR non-major: 1 | SO: 6 | FR: X |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 0 | 1st Ranked: 0 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 0 |
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