LIS 542

Spring 2017 All Classes

All Classes

Data, Stat, Info

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Credit: 4 hours.

An introduction to statistical and probabilistic models as they pertain to quantifying information, assessing information quality, and principled application of information to decision making, with focus on model selection and gauging model quality. The course reviews relevant results from probability theory, parametric and non-parametric predictive models, as well as extensions of these models for unsupervised learning. Applications of statistical and probabilistic models to tasks in information management (e.g. prediction, ranking, and data reduction) are emphasized.

4 graduate hours. No professional credit. Prerequisite: Graduate standing.

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LIS 542 class schedule data for spring 2017
	CRN	Type	Section	Time	Day	Location	Instructor	Section Details
	63691	Lecture-Discussion	A	9:00AM -11:50AM	T	Grad Sch of Lib & Info Science	Stodden, V	Part of Term: 1 Date Range: 01/17/17-05/03/17 Section Info: An introduction to statistical and probabilistic models as they pertain to quantifying information, assessing information quality, and principled application of information to decision-making, with a focus on model selection and gauging model quality. The course reviews relevant results from probability theory, parametric and non-parametric predictive models, as well as extensions of these models for unsupervised learning. Applications of statistical and probabilistic models to tasks in information management (e.g. prediction, ranking, and data reduction) are emphasized Restriction(s): Restricted to students in the Information Sciences department.
	65855	Online	LE	5:30PM -7:30PM	R	n.a.	Stodden, V	Part of Term: 1 Date Range: 01/17/17-05/03/17 Section Info: Restricted to graduate students in the School of Information Sciences. All other students need department approval. Email ischool-advising@illinois.edu This is a required course for the MSIM degree. Restriction(s): Restricted to students in the Information Sciences department.