MATH4240 - Stochastic Processes - 2020/21

Course Name: 
Course Year: 


  • Jan 4: Welcome to this course! Check your Blackboard to get the zoom information. No tutorial in the 1st week. Here is the tentative course plan (Recorded course lectures also will be updated inside; please click the link and login your University account to get them): [Download file]
  • Jan 27: The tutorial lecture on Feb 8th will change to the course lecture. Thus, the course lecture on Feb 8th will start at 12:30pm and end at 2:15pm. Please join it with the same zoom information.
  • Feb 8: One course lecture will be added on Feb 20 (Saturday) at 9:30am-12:00noon, with the zoom information the same as the usual one. The course lecture on Feb 22 (Monday) will be cancelled (but the tutorial on that day is still on schedule).
  • March 8: Arrangement for Midterm Test: [Download file]
  • April 2: The final exam will be still held as a take-home test for 24 hours, starting at 10:00am, May 10th and ending at 10:00am, May 11th. Like the midterm test, it is expected that the questions can be finished within 3 hours, and as such, the 24-hours limit should allow enough flexibility. ┬áThe further details will be announced in due course.
  • April 12: Please be reminded to complete the online CET questionaire to our course in the stipulated time period from 2:30pm April 14th to 4:15pm April 15th. To get the link for doing this, please refer to the email you received from MATH department on April 12th. Thank you for your help and support.
  • April 29: Arrangement for Final Exam: [Download file]

General Information


  • Prof. Renjun DUAN
    • Office: LSB 206
    • Tel: 39437977
    • Email:

Teaching Assistant

  • Mr. Wing Hong WONG
    • Office: LSB 222A
    • Tel: 39433575
    • Email:

Time and Venue

  • Lecture: Mo 1:30PM - 2:15PM (Online); We 2:30PM - 4:15PM (Online)
  • Tutorial: Mo 12:30PM - 1:15PM (Online)

Course Description

Bernoulli processes and sum of independent random variables, Poisson processes, times of arrivals, Markov chains, transient and recurrent states, stationary distribution of Markov chains, Markov pure jump processes, and birth and death processes. Students taking this course are expected to have knowledge in probability.


  • Introduction to Stochastic Processes by Hoel, Port and Stone (Chapter 1, Chapter 2, and Chapter 3 ONLY)


  • Essentials of Stochastic Processes by Durrett (many applied examples)
  • Introduction to Stochastic Processes by Lawler (condense)
  • Basic Stochastic Processes by Brzezniak and Zastawniak (more theoretical)
  • Denumerable Markov chains by Wolfgang Woess (more topics on Markov chains)
  • Stochastic Processes by Sheldon Ross (more advanced)

Pre-class Notes

Lecture Notes

Class Notes

Tutorial Notes


Quizzes and Exams


Useful Links

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and thereby help avoid any practice that would not be acceptable.

Assessment Policy

Last updated: May 10, 2021 08:32:11