Introduction to Linear Models
STAT 139
Subject & Catalog Number
Course Information
Description
An in-depth introduction to statistical methods with linear models and related methods. Topics include group comparisons (t-based methods, non-parametric methods, bootstrapping, analysis of variance), linear regression models and their extensions (ordinary least squares, ridge, LASSO, weighted least squares, multi-level models), model checking and refinement, model selection, cross-validation. The probabilistic basis of all methods will be emphasized.
Recommended Prep
Statistics 110 and Math 21a and 21b or equivalent (Math 21b can be taken concurrently). Statistics 111 and some familiarity with R are recommended.
Available for Harvard Cross Registration
NOTE: This course requires additional sections; you will be prompted to choose secondary components during the Add to Cart process
