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MATH 5110

Introduction to Stochastic Processes

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Course Description

Pre-Requisite(s): MATH 3100 and a knowledge of matrix algebra, or instructor permission

Topics in probability selected from Random walks, Markov processes, Brownian motion, Poisson processes, branching processes, stationary time series, linear filtering and prediction, queuing processes, and renewal theory.


  • Leonid Petrov
     Rating

    5.00

     Difficulty

    3.00

     GPA

    3.79

     Sections

    —

    Last Taught

    Spring 2015

  • Rajinder Mavi
     Rating

    4.33

     Difficulty

    4.00

     GPA

    3.19

     Sections

    —

    Last Taught

    Spring 2014

  • Hans Gromoll
     Rating

    3.50

     Difficulty

    3.50

     GPA

    3.40

     Sections

    —

    Last Taught

    Fall 2014

  • Lawrence Thomas
     Rating

    —

     Difficulty

    —

     GPA

    3.16

     Sections

    —

    Last Taught

    Spring 2012

  • Tai Melcher
     Rating

    3.89

     Difficulty

    3.67

     GPA

    3.20

     Sections

    —

    Last Taught

    Fall 2011