IEOR E6711 Stochastic models, I. 4.5 points.
Prerequisites: (STAT GU4001) or Refer to course syllabus.
This is the first course in a two-course sequence introducing students to the theory of stochastic processes. The fall term starts with a review of probability theory and then treats Poisson processes, renewal processes, discrete-time Markov chains and continuous-time Markov chains. The spring term emphasizes martingales and Brownian motion. Although the course does not assume knowledge of measure theory or measure-theoretic probability, the focus is on the mathematics. Proofs are emphasized. This course sequence is intended for our first-year doctoral students. Indeed, one of the two qualifying exams at the end of the first year covers the material taught in this course sequence. The course is intended to provide students background, so that they will be able to effectively conduct research.
Fall 2019: IEOR E6711
|Course Number||Section/Call Number||Times/Location||Instructor||Points||Enrollment|
|IEOR 6711||001/10279||M W 11:40am - 12:55pm
644 Seeley W. Mudd Building