STAT/MATH 416, Section 001, Fall 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, the Gambler's Ruin Problem, reliability theory, continuous-time
Markov chains, with applications 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, 10:35 - 11:50 a.m., Waring Hall 129
    • Office Hours: Tue/Thu, 3:00 - 3:30 p.m.
    • Office: 311 Thomas Building

  • Zhe Zhang, Teaching Assistant
    • Office Hours: Wed/Fri, 2:00 - 3:00 p.m.
    • Office: 301 Thomas Building

Course Information



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