STAT/MATH 416, Section 001, Spring 2019

    Stochastic Modeling (Stochastic Processes)

This course introduces students to the theory and applications of stochastic processes. Topics
covered in the course include conditional probability and conditional expectation, Markov
chains, the Poisson process, continuous-time Markov chains, Brownian motion, and various
applications of these concepts to actuarial science, biology, insurance, and other fields.
During the course, we will monitor the New York Times and Centre Daily Times newspapers
for articles involving probability and stochastic processes. We will study the probabilistic
information in such articles and relate them to the course and to everyday life.

Contact Information

  • Donald Richards, Instructor
    • Class: Tue/Thu, 9:05 - 10:20 a.m., 108 Forum Bldg.
    • Office Hours: Tue/Thu, 10:40 - 11:40 a.m.
    • Office: 311 Thomas Building

  • Haoyi Yang, Teaching Assistant
    • Office Hours: Mon/Wed, 4:00 - 5:00 p.m.
    • Office: 333 Thomas Building

Course Information

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