Advanced Regression and Statistical Learning
BST 235
Subject & Catalog Number
Jointly Offered with:
Faculty of Arts & Sciences as BIOSTAT 235
Course Information
Description
An advanced course in linear models, including both classical theory and methods for high dimensional data. Topics include theory of estimation and hypothesis testing, multiple testing problems and false discovery rates, cross validation and model selection, regularization and the LASSO, principal components and dimensional reduction, and classification methods. Background in matrix algebra and linear regression required.
Course Note: Lab or section times to be announced at first meeting; cross-listed: Harvard Chan Students must register for the Harvard Chan course.
School
Harvard Chan School
Credits
5
Cross Reg
Available for Harvard Cross Registration
Subject
Biostatistics
Grading Basis
HSPH Student Option (Audit, Ordinal, Pass/Fail)
Course Requirements
Pre-requisites: BST231 and (BST 232 or BST233).
