Summer 2023 - CMPT 210 D100

Probability and Computing (3)

Class Number: 3955

Delivery Method: In Person


  • Course Times + Location:

    Mo, We, Fr 9:30 AM – 10:20 AM
    AQ 3153, Burnaby

  • Prerequisites:

    MACM 101, MATH 152, and MATH 240, all with a minimum grade of C-.



Probability has become an essential tool in modern computer science with applications in randomized algorithms, computer vision and graphics, systems, data analysis, and machine learning. The course introduces the foundational concepts in probability as required by many modern applications in computing.


The course introduces the foundational concepts in probability as required by many modern applications in computing. It will give computing students experience in: 1. Understanding the combinatorial nature of many computational problems. 2. Working knowledge of probability theory, with applications to computing (e.g., algorithms, machine learning, data analysis, etc.).


  • Combinatorics: Permutations, Binomial coefficients, Inclusion-Exclusion
  • Basic probability theory: Independence, Conditional probability, Bayes' Theorem
  • Basic probability theory: Random variables, Expectation, Linearity of Expectation, Variance
  • Discrete distributions: Binomial and Geometric, Joint distributions
  • Tail inequalities: Markov’s Inequality, Chebyshev’s Inequality, Chernoff Bound
  • Applications: Verifying matrix multiplication, Max-Cut, Machine Learning, Randomized QuickSort, AB Testing
  • Continuous distributions (Introduction): Normal Distribution, Central Limit Theorem



There will be multiple evaluations, the details of which to be discussed in the first week of classes.

Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C− or better).



Reference Books

  • Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, Sheldon M. Ross, 978-0128243466

Registrar Notes:


SFU’s Academic Integrity website 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.