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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

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


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

Unit Designation(s):


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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