This course will cover the mathematical theory of probability. The topics covered will include basic notions of probability, conditional probability,independence and Bayes law, various discrete and continuous random
variables, expectation, variance and moment, joint probability distributions, Chebyshev's inequality, the
law of large numbers, and the central limit theorem. Markov chain (if time available.)
There are 13 weeks of lectures from Jan 18th to Apr 28th.
The two in-term exams will be scheduled on Feb 20th and April 10th.
Homework will be updated at this website weekly.
A detailed schedule will be updated here. The materials will be covered each week will be adjusted based on the pace.