MATH4240 - Stochastic Processes - 2020/21
Announcement
- 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. The 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
Lecturer
-
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.
Textbooks
- Introduction to Stochastic Processes by Hoel, Port and Stone (Chapter 1, Chapter 2, and Chapter 3 ONLY)
References
- 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
- Zoom Note01 (updated on 0113)
- Zoom Note02 (updated on 0120)
- Zoom Note03 (updated on 0125)
- Zoom Note04 (updated on 0201)
- Zoom Note05 (updated on 0203)
- Zoom Note06 (updated on 0210)
- Zoom Note07-part1 (updated on 0220)
- Zoom Note07-part2 (updated on 0224)
- Zoom Note08 (updated on 0303)
- Zoom Note09 (updated on 0308)
- Zoom Note10 (updated on 0310)
- Zoom Note11 (updated on 0317)
- Zoom Note12 (updated on 0322)
- Zoom Note13 (updated on 0324)
- Zoom Note14 (updated on 0327)
- Zoom Note15 (updated on 0327)
- Zoom Note16 (updated on 0414)
- Zoom Note17 (updated on 0419)
- Zoom Note18 (updated on 0419)
- Zoom Note19 (updated on 0421)
Class Notes
Tutorial Notes
- Tutorial 1
- Tutorial 2
- Tutorial 3
- Tutorial 4
- Tutorial 5
- Tutorial 6
- Tutorial 7
- Tutorial 8
- Tutorial 9
- Tutorial 10
Assignments
- Homework 01
- Homework 02
- Homework 03 (due date extended to March 5th)
- Homework 04
- Homework 05
- Homework 06
- Homework 07
- Homework 08
- Final report
Quizzes and Exams
- Midterm Test: Front page and answer sheet template
- Midterm Test: Question paper
- Final Exam: Front page and answer sheet template
- Final Exam: Question paper
Solutions
- Solution 1
- Solution 2
- Solution 3
- Solution 4
- Solution Midterm
- Solution 5
- Solution 6
- Solution 7
- Solution 8
Useful Links
- Probability, Mathematical Statistics, Stochastic Processes (An open source) [Link]
- Essentials of Stochastic Processes (Richard Durrett) [Link]
- Markov Chains (James Norris) [Link]
- A First Course in Probability (Sheldon Ross) [PDF]
Honesty in Academic Work
The Chinese University of Hong Kong places very high importance on honesty in academic work submitted by students, and adopts a policy of zero tolerance on cheating and plagiarism. Any related offence will lead to disciplinary action including termination of studies at the University. Although cases of cheating or plagiarism are rare at the University, everyone should make himself / herself familiar with the content of the following website:
http://www.cuhk.edu.hk/policy/academichonesty/and thereby help avoid any practice that would not be acceptable.
Assessment Policy Last updated: May 10, 2021 08:32:11