Spring 2025 - STAT 380 D100

Introduction to Stochastic Processes (3)

Class Number: 2246

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2025: Mon, Wed, Fri, 9:30–10:20 a.m.
    Burnaby

  • Exam Times + Location:

    Apr 14, 2025
    Mon, 12:00–3:00 p.m.
    Burnaby

  • Prerequisites:

    STAT 330, or all of: STAT 285, MATH 208W, and MATH 251, all with a minimum grade of C-.

Description

CALENDAR DESCRIPTION:

Review of discrete and continuous probability models and relationships between them. Exploration of conditioning and conditional expectation. Markov chains. Random walks. Continuous time processes. Poisson process. Markov processes. Gaussian processes. Quantitative.

COURSE DETAILS:

Course Outline:

  1. Probability review
  2. Markov chains
  3. Branching process
  4. Poisson process
  5. Queuing theory or Renewal theory (time-permitting)
  6. Brownian motion
  7. Markov chain Monte Carlo similation
  8. Generative diffusion models
Assessment & Grade Distribution: Evaluation of student-performance in this
course consists of a few components:

• 10% of the course-grade will be on short quizzes posed after selected lectures
that must be completed within 24 hours of the lecture. The question(s) will
be related to an important point or observation made during the lecture.

• 30% of the grade will be on homework assignments. Grades will be determined
by both correctness of analysis and presentation of results. The
projects are worth varying amounts of points depending on difficulty and
length. Assignments will be given toward the completion of each module in
the course, that is, roughly 1 to 2 weeks.

• There will be one mid-term test (in-class) worth 20% of the grade and an
end-semester final worth 30%.

• The remaining 10% will be on a short project toward the end of the semester.
         We will discuss this further on the first day of classes.

Clarity of presentation and explanation is an important part of the evaluation of course-work.

A major portion of student-assessment is based on periodic modeling and analysis
exercises assigned as homework and to be carried out using techniques discussed
in class. The lectures present the theory and demonstrate examples. Tightly coordinated
with the lectures, the weekly tutorial sessions explain how the examples
covered in class were computed, present additional examples, and general information
useful for completing the homework exercises should attending students
ask for help. Success in the course depends on attending lectures and tutorials.

Stipulation for collaboration on and submission of assignments and tests:

• You may work with other students enrolled in the course provided you list
them on the cover page of your assignment.

• You may not consult with anyone external to the course for assistance or help
with a course assignment or test. For example, this includes personal tutors
and students not enrolled in the course.

• The final submissions must be written (or typed) on your own. Even if two or
more students in the course collaborate on an assignment, each will still have
to submit their own reports written independently and in their own words.

• You must complete the cover page properly. Points will be deducted if the
cover page is incomplete or unsigned.

• There will be no collaboration in the in-class tests.

• Policy regarding use of generative AI tools for writing will be discussed on
the first day of classes.

Failure to comply with these restrictions or failure to list all resources used to
complete an assignment is considered a very serious breach academic honesty.

Grading

  • Assignments/Quizzes/Tests/Project 60%
  • Final Exam 40%

NOTES:

Above grading is subject to change.

Materials

RECOMMENDED READING:

Introduction to Probability Models (12th Edition) by: S.M. Ross. Publisher: Academic Press

Book is available through the SFU Bookstore


REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Department Undergraduate Notes:

Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or caladmin@sfu.ca.  


Tutor Requests:
Students looking for a tutor should visit https://www.sfu.ca/stat-actsci/all-students/other-resources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html

RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.