Statistics

STAT 205 Introduction to Classical Statistical Learning

Introduction to classical statistical inference. Topic include: random variables and distributions; types of convergence; central limit theorems; maximum likelihood estimation; Newton-Raphson, Fisher scoring, Expectation-Maximization, and stochastic gradient algorithms; confidence intervals; hypothesis testing; ridge regression, lasso, and elastic net.

Requirements

Prerequisite(s): STAT 203. Enrollment is restricted to graduate students.

Credits

5