Courses Detail Information

ECE4010J – Probabilistic Methods in Engineering


Horst Harold Hohberger

Credits: 4 credits

Pre-requisites: MATH2160J Obtained Credit||MATH2560J Obtained Credit||MATH2860J Obtained Credit


This first course in probability and statistics gives a broad introduction to the field. The focus is on conveying fundamental concepts that will prepare students for more advanced courses in statistics (Bayesian statistics, advanced regression) as well as in applied fields (data analytics, machine learning, financial mathematics). The course emphasizes rigorous mathematics (a solid background in multivariable calculus and familiarity with matrices, determinants, eigenvalues etc. is assumed), a deep understanding of the relevant concepts, and the meaning and interpretation of mathematical results in statistics in real life.

Course Topics:

  1. Elementary probability (4 hrs at 45 min each)
  2. Discrete and continuous random variables with applications. (16 hours)
  3. Statistical sampling, data visualization, parameter estimation (8 hours)
  4. Hypothesis Testing (Fisher and Neyman-Pearson) in various settings (16 hours)
  5. Simple and Multiple Linear Regression (8 hours)
  6. Analysis of Variance (4 hours)
  7. Two exams (4 hours)