Probability Introduction

This course introduces fundamental concepts of probability, including sample spaces and events, conditional probability, independence, and Bayes’ theorem. It covers discrete and continuous random variables, common distributions (Bernoulli, Binomial, Poisson, Normal), joint distributions, expectation, variance, covariance, and moment generating functions. Foundational limit theorems such as the Law of Large Numbers and Central Limit Theorem are discussed, with applications to basic statistical inference.

As a teaching assistant (TA), my responsibilities included grading assignments, leading exercise sessions and supplementary tutorials, grading midterm and final exams, and providing regular Q&A support and office hours.