Ma104a Probability

I taught this course in Winter 2022 and Winter 2024. The material here corresponds to the 2024 iteration of the course.

Syllabus: contains description of course’s scope, methodology, guiding principles, learning outcomes, references, coursework, grading, collaboration policy and academic integrity.

Slides used in lectures:

• Random variables
• Moments and the law of large numbers
• The central limit theorem
• Conditional probabilities and expectation
• Markov chains

Blog post:

• Komogorov’s axiomatization of probability

Scripts:

• Google Colab illustrating the law of large numbers and the central limit theorem

Weekly problem sets used for collaborative problem-solving sessions and homework assignments:

• Workshop 1: Events
• Workshop 2: Independence
• Workshop 3: Integration
• Workshop 4: Moments and the law of large numbers
• Workshop 5: Central limit theorem
• Workshop 6: Conditional probability
• Workshop 7: Martingales
• Workshop 8: Martingale convergence
• Workshop 9: Markov chains, martingales and potential theory