DEPARTMENT of MATHEMATICS and STATISTICS
Courses
We take pride in our students’ accomplishments, from first-year learners in required courses to upper-year students pursuing their passion for numbers.
Our department offers courses in the disciplines listed below. For individual course descriptions, follow the links to MacEwan University’s Academic Calendar.
Not all courses are available each term. Courses must be numbered 100 and above to be used to fulfill degree requirements.

Special topics
Special topics courses focus on specific areas of interest within a discipline. The topics are chosen based on the expertise of our instructors, and the topics usually vary from term to term.
Winter 2025
Course: STAT 395: Special Topics in Statistics | Survival Analysis
Term: Winter 2025
Section: AS01
Instructor: David Thiessen
Basic Concepts for Survival Data, Kaplan-Meier and Nelson-Aalan Estimators, Parametric Methods for Lifetime Distributions, Regression Models, Model Checking and Goodness-of-Fit Tests
Prerequisites: A minimum grade of C- in STAT 266 and a minimum grade of C- one of STAT 371 or STAT 378, or consent of the department.
Permission Required: Yes. To enrol in this class, please contact the Department Chair, Dr. Adi Tcaciuc at TcaciucA@macewan.ca to request a permission number.
Fall 2025
Course: MATH 495: Special Topics in Mathematics | The Lebesgue Integral
Term: Fall 2025
Section: AS01
Instructor: Dr. Cristian Ivanescu
The course provides an introduction to the Lebesgue Integral. The basic properties of the integral are developed, and the fundamental theorems concerning convergence are covered. Related concepts such as the Lebesgue measure, Borel sets, measurable functions and non-measurable sets are discussed.
Prerequisites: A minimum grade of C- in a MATH 310-level MATH course and consent of the department.
Permission Required: Yes. Please email the Chair (tcaciuca@macewan.ca) to obtain a permission number.
Course: STAT 495: Special Topics in Statistics | Introduction to Causal Inference
Term: Fall 2025
Section: AS01
Instructor: Dr. Rui Hu
This course explores causal inference methods for randomized experiments and observational studies, covering key topics such as sensitivity analysis, instrumental variables and mediation analysis. Students will learn to address challenges like unmeasured confounding and apply rigorous techniques to real-world problems across various disciplines.
Prerequisites: A minimum grade of B- in a 300-level STAT course and consent of the department.
Permission Required: Yes. Please email the Chair (tcaciuca@macewan.ca) to obtain a permission number.