STAT 432

Spring 2023 All Classes

All Classes

Basics of Statistical Learning

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Credit: 3 OR 4 hours.

Topics in supervised and unsupervised learning are covered, including logistic regression, support vector machines, classification trees and nonparametric regression. Model building and feature selection are discussed for these techniques, with a focus on regularization methods, such as lasso and ridge regression, as well as methods for model selection and assessment using cross validation. Cluster analysis and principal components analysis are introduced as examples of unsupervised learning.

Same as ASRM 451. 3 undergraduate hours. 4 graduate hours. Prerequisite: STAT 400, and either STAT 420 or STAT 425.

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STAT 432 class schedule data for spring 2023
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	67118	Lecture-Discussion	1GR	9:30AM -10:50AM	TR	3031 Campus Instructional Facility	Lee, H	Part of Term: 1 Date Range: 01/17/23-05/03/23 Credit: 4 hours Section Info: For Statistics course registration information: go.illinois.edu/StatisticsRegistration. Restriction(s): Restricted to Graduate - Urbana-Champaign.
	67119	Lecture-Discussion	1UG	9:30AM -10:50AM	TR	3031 Campus Instructional Facility	Lee, H	Part of Term: 1 Date Range: 01/17/23-05/03/23 Credit: 3 hours Section Info: For Statistics course registration information: go.illinois.edu/StatisticsRegistration. Restriction(s): Restricted to Undergrad - Urbana-Champaign.