Covers statistical methods for learning from data beyond those typically learned in introductory courses. Emphasis on statistical modeling, including multiple linear regression, classification models, and other methods for supervised learning and statistical inference. Additional techniques include non-parametric methods, bootstrap estimation, and analysis of model fit via cross-validation. Includes a strong computational component and will make use of the statistical programing language R for data analysis and simulations.

Prerequisite: Mathematics 217 or (Mathematics 117 and Mathematics 126).

1 unit — Sancier-Barbosa

Offerings

Term	Block	Title	Instructor	Location	Student Limit/Available	Updated
Fall 2023	Block 3	Statistical Methods I	Flavia Sancier-Barbosa	TBA	25 / 22	09/27/2023