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Generalized Linear Models - STAT811

This unit starts with the classical normal linear regression model. The family of generalized linear models is then introduced and maximum likelihood estimators are derived. Models for counted responses, binary responses, continuous non-normal responses and categorical responses; and models for correlated responses, both normal and non-normal, and generalised additive models, are studied. Zero-inflated models are also considered. All models and methods are illustrated using data sets from disciplines such as biology, actuarial studies and medicine.

Credit Points: 4
When Offered:

S2 Evening - Session 2, North Ryde, Evening

S2 External - Session 2, External (with on campus sessions)

Staff Contact(s): Statistics Staff
Prerequisites:

(Admission to MAppStat or MSc or GradCertAppStat or GradDipAppStat or MActPrac or MDataSc or MScInnovation and (STAT806 or STAT810)) or (admission to MMarScMgt or MConsBiol or GradDipConsBiol and STAT830(Cr)) Prerequisite Information

Corequisites:

NCCW(s):
Unit Designation(s):

Commerce

Science

Assessed As: Graded
Offered By:

Department of Mathematics and Statistics

Faculty of Science and Engineering

Course structures, including unit offerings, are subject to change.
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