![]() ![]() prereq: 5651 or Stat 5101 Class Description: This course in one of three courses designed to follow Math 5651/Stat 5101, the 'two' courses Math 5651 and Stat 5101 being the same course. ![]() Class Format: 90% Lecture 10% Discussion Workload: 30 Pages Reading Per Week 3 OR 4 Exam(s) Textbooks: Instructor Supplied Information Last Updated: Ĭourse Catalog Description: Random walks, Markov chains, branching processes, martingales, queuing theory, Brownian motion. Exam Format: Problem solving and proofs, both of which often require essay-type responses. ![]() An approximate guide on this issue is: 'yes' if that probability course has a multivariable calculus prerequisite and 'no' if not. Students who have had a probability course elsewhere might wonder whether that course will be sufficient to stand in lieu of the prerequisite Math 5651/Stat 5101. The intended audience includes undergraduate and Master's students in mathematics, and undergraduate and graduate students in engineering and the physical and social sciences. Calculation and theoretical aspects of these stochastic processes will be treated. Various names are associated with these sequences and processes according to the assumptions being made about the interrelation among the random values at various times: Markov sequences, martingales, Markov process, queuing theory, branching processes, Brownian motion. Math 5652 is concerned with random sequences and random processes, with the independent variable typically interpreted as time. The courses Math 5652, Math 5654, and Stat 5102 are all distinct from each other, and taking one of them does not preclude taking the other one or two for credit. The other two courses designed to follow Stat 5101/Math 5651 are Math 5654, Prediction and Filtering, and Stat 5102, Theory of Statistics II. Course Catalog Description: Random walks, Markov chains, branching processes, martingales, queuing theory, Brownian motion. ![]()
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