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Stochastic Processes MATH 233 Spring 2027 Section: 01   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. Credit: 1 Gen Ed Area Dept: NSM MATH Course Format: Lecture Grading Mode: Graded Level: UGRD Prerequisites: MATH231 Fulfills a Requirement for: (Applied Data Science Certificate)(Data Analysis Minor)(Mathematics) Past Enrollment Probability: Not Available SECTION 01 Instructor(s): Ramirez,Felipe          Times: .M.W... 01:20PM-02:40PM;       Location: TBA Total Enrollment Limit: 25 SR major: 9 JR major: 9     Seats Available: 25 GRAD: X SR non-major: 0 JR non-major: 2 SO: 2 FR: 2 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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