08. Lecture notes

Lecture notes 1 (Set theory)

Lecture notes 2 (Probabilistic model, axioms and probability laws)

Lecture notes 3 (Conditional probability)

Lecture notes 4 (Conditional probability and multiplication law)

Lecture notes 5 (Total probability formula and Bayes Theorem)

Lecture notes 6 (Independence and conditional independence)

Lecture notes 7 (Independence of multiple events)

Lecture notes 8 (The counting principle)

Lecture notes 9 (Probability mass function)

Lecture notes 10 (Geometric and Poisson distribution)

Lecture notes 11 (Expected value and variance)

Lecture notes 12 (Joint probability mass function)

Lecture notes 13 (Conditioning via pmf)

Lecture notes 14 (Independence via pmf)

Lecture notes 15 (Continuous PDF, expectation, and exponential distribution*)

Lecture notes 16 (CDF and normal distribution)

Lecture notes 17 (Joint PDF)

Lecture notes 18 (Independence)