Advanced Regression and Statistical Learning
BIOSTAT 235
Subject & Catalog Number
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 dimension reduction, and classification methods. Background in matrix algebra and linear regression required.
Course Notes
Offered jointly with the School of Public Health as BST235.
School
Faculty of Arts & Sciences
Credits
4
Cross Reg
Available for Harvard Cross Registration
Department
Biostatistics
Course Component
Lecture
Subject
Biostatistics
Grading Basis
FAS Letter Graded
Course Requirements
Prerequisite: Biostatistics 231 AND Biostatistics 232
General Education
N/A
Quantitative Reasoning with Data
N/A
Divisional Distribution
Science & Engineering & Applied Science
Course Level
Primarily for Graduate Students
