Overview

Regression is a set of statistical techniques widely used to analyse relationships between several variables. The topics covered in this course include: linear regression; weighted least squares; generalized linear models (GLMs); fitting GLMs and examining model diagnostics; Poisson regression, binomial regression; analysis of variance; penalized regression methods; splines; penalized splines; … For more content click the Read More button below. Lectures will be complemented with worked examples where students will perform data analysis and statistical programming using the R software.

Delivery

In-person - Standard (usually weekly or fortnightly)

Course Outline

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Fees

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)