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Linear Models - BCA808

The aim of this unit is to enable students to apply methods based on linear models to biostatistical data analysis, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results. The following topics are covered: the method of least squares; regression models and related statistical inference; flexible nonparametric regression; analysis of covariance to adjust for confounding; multiple regression with matrix algebra; model construction and interpretation (use of dummy variables, parametrisation, interaction and transformations); model checking and diagnostics; regression to the mean; handling of baseline values; the analysis of variance; variance components and random effects.

Because of the multi-institutional nature of the BCA units, there is an early cut-off for enrolment in this unit. These dates are:
Session 1: 19 February 2018
Session 2: 23 July 2018

Credit Points: 4
When Offered:

S1 Online - Session 1, Online

S2 Online - Session 2, Online

Staff Contact(s): Professor Gillian Heller
Prerequisites:

((Admission to MBioStat or GradDipBioStat or GradCertBioStat) and BCA801 and BCA817) or (admission to MActPrac and (STAT810 or STAT806)) Prerequisite Information

Corequisites:

((Admission to MBioStat or PGDipBioStat or PGCertBioStat or GradDipBioStat or GradCertBioStat) and BCA805) or admission to MActPrac

NCCW(s):
Unit Designation(s):

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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