Statistical Estimation: This is a proof-based, graduate or advanced undergraduate level introduction to statistical estimation. The goal of this one-semester course is to introduce basic approaches in mathematical statistics, including the minimax and the Bayesian point of view coupled with either asymptotic or finite-sample analysis. The lecture notes were written in a mostly rigorous and self-contained way, but with some measure-theoretic details left out. They should be readable to students with a solid background in probability theory and provide a fast alternative to classic books.
Hypothesis Testing: This is a proof-based, graduate or advanced undergraduate level introduction to hypothesis testing. Lecture notes are under development.
Introductory Probability and Statistics: This is an undergraduate level introduction to probability and statistics for engineering students. Lecture notes are under development.