STAT 342
Introduction to Stochastic Processes Fall 2019
Division III Quantative/Formal Reasoning

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Stochastic processes are mathematical models for random phenomena evolving in time or space. Examples include the number of people in a queue at time t or the accumulated claims paid by an insurance company in an interval of time t. This course introduces the basic concepts and techniques of stochastic processes used to construct models for a variety of problems of practical interest. The theory of Markov chains will guide our discussion as we cover topics such as martingales, random walks, Poisson process, birth and death processes, and Brownian motion.
The Class: Type: lecture
Limit: 30
Expected: 15
Class#: 1616
Grading: yes pass/fail option, yes fifth course option
Requirements/Evaluation: primarily on weekly homework, classwork, and exams
Prerequisites: STAT 341
Enrollment Preferences: senior Statistics majors
Distributions: Division III Quantative/Formal Reasoning
QFR Notes: This is a statistics class with a focus on mathematical skills and translating real world phenomena into mathematical descriptions.

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