MA237 - Statistical Methods I

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. Meets the Critical Learning: FRL requirement. Meets the Critical Learning: SA requirement.

Prerequisite: Mathematics 217 or (Mathematics 117 and either Mathematics 125 or Mathematics 126).

1 unit — Kim, Sancier-Barbosa


Term Block Title Instructor Location Student Limit/Available Updated
Fall 2023 Block 3 Statistical Methods I Flavia Sancier-Barbosa Mathias Hall Classroom 25 / 19 06/23/2024
Fall 2024 Block 1 Statistical Methods I Flavia Sancier-Barbosa TBA 25 / 16 06/23/2024
Spring 2025 Block 6 Statistical Methods I Minho Kim TBA 25 / 25 06/23/2024
Report an issue - Last updated: 06/23/2024