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.

Conditions for Enrolment

Enrolment in program 5659 or 8161 or 8719 or 8750 or 8959 or 7659

Delivery

In-person - Standard (usually weekly or fortnightly)

Fees

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)