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BST 235 - Advanced Regression and Statistical Learning or return to Course Catalog Search

190052 – Section 1   

SchoolDepartmentFaculty
Harvard T.H. Chan School of Public HealthBiostatisticsTianxi Cai
TermDay and TimeLocation
Fall (Full Semester) 2017  (show academic calendar)MW   9:45 a.m. - 11:15 a.m.Kresge 201 (HSPH)
Credits
5  (show credit conversion for other schools)
Credit Level
Graduate

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.Prerequisite: BST 231 and BST 233, or permission of instructor required.Formerly BIO235

Prerequisite(s)
HSPH: BST235

 
Cross Registration
Eligible for cross-registration
With permission of instructor/subject to availability

MIT students please cross register from MIT's Add/Drop application.

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