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Statistical Learning and Prediction STAT 652 (3)

An introduction to the essential modern supervised and unsupervised statistical learning methods. Topics include review of linear regression, classification, statistical error measurement, flexible regression and classification methods, clustering and dimension reduction. Open only to graduate students in departments other than Statistics and ActSci. Prerequisite: STAT 302 or STAT 305 or STAT 350 or ECON 333 or equivalent. Students with credit for STAT 452 may not take this course for further credit.

Section Instructor Day/Time Location
G100 Haolun Shi
Tu 10:30 AM – 12:20 PM
Fr 10:30 AM – 11:20 AM
REMOTE LEARNING, Burnaby
REMOTE LEARNING, Burnaby
G101 Tu 8:30 AM – 9:20 AM
REMOTE LEARNING, Burnaby
G102 Tu 9:30 AM – 10:20 AM
REMOTE LEARNING, Burnaby
G103 Tu 4:30 PM – 5:20 PM
REMOTE LEARNING, Burnaby
G104 Tu 5:30 PM – 6:20 PM
REMOTE LEARNING, Burnaby
G105 Tu 6:30 PM – 7:20 PM
REMOTE LEARNING, Burnaby