Middlebury

STAT 0218

Statistical Learning

Statistical Learning (formerly MATH 0218)
This course is an introduction to modern statistical, machine learning, and computational methods to analyze large and complex data sets that arise in a variety of fields, from biology to economics to astrophysics. The theoretical underpinnings of the most important modeling and predictive methods will be covered, including regression, classification, clustering, resampling, and tree-based methods. Student work will involve implementation of these concepts using open-source computational tools. (MATH 0118 or STAT 0118 or STAT 0201 or MATH 0216 or BIOL 1230 or ECON 1230 or ENVS 1230, or FMMC 1230 or HARC 1230 or JAPN 1230 or LNGT 1230 or NSCI 1230 or MATH 1230 or SOCI 1230or WRPR 1230 or GEOG 1230) 3 hrs. lect./disc.
Subject:
Statistics
Department:
Mathematics & Statistics
Division:
Natural Sciences
Requirements Fulfilled:
DED
Equivalent Courses:
MATH 0218

Sections in Spring 2024, School Abroad Spain (Madrid)

Spring 2024

STAT0218A-S24 Lecture (Lyford)