Course Syllabus

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Course Objective:  To introduce some key ideas, applications and methods of stochastic modeling and problem solving in a very concise but a mathematically precise way. 

Main Topics: 

  • Random walks
  • Martingales
  • Poisson processes
  • Branching processes
  • Discrete-time Markov chains
  • Markov jump processes
  • Mathematical Brownian motion, diffusion processes, and Ito calculus (if time permits).

Prerequisites: (STA260H5 or STA261H5) and (MAT223H5 or MAT240H5).

In particular, students are expected to have a good understanding of the following: 

  • Mathematical proofs
  • Basic probability theory and statistics
  • Differential and integral calculus
  • Basic linear algebra

Textbook:  D. Stirzaker, Stochastic Processes and Models, Oxford University Press.

The PDF version of the textbook is freely available through the UTM Library. To access the book follow this link and login using your UTORid. You can download parts of the textbook for individual use. You are not required to purchase a physical copy of the book. 

 

Course Summary:

Date Details Due