Broadly, this course is focused on mathematical statistics. We will most likely cover the following topics: Basics of probability: expectations, conditional expectations, probability distributions, moments, tranformations of random variables, moment generating functions. Concentration inequalities: Markov, Chebyshev, Hoeffding inequalities, and their uses in statistics. Central limit theorem, delta method. Point estimation and its properties: likelihood, MLE, Fisher Information, Cramer-Rao bound, decision theory.