STAT202-12S2 (C) Semester Two 2012
Regression Modelling

Description

This course is of interest to students majoring in statistics, as well as students from other
disciplines (e.g. biology, commerce, etc.) who want to increase the breadth of their statistical
knowledgebase. Regression models are the most widely used statistical tools for examining the relationships among variables. We cover the core concepts in regression modelling, with an emphasis on problem solving as applied to real data. The computer package R is used, one of the mostly widely used statistical packages, but no prior knowledge of R is assumed. Students on this course may also be interested in STAT201/FORE222 Applied Statistics, although it is not a pre-requisite.

Learning Outcomes

• be able to use R/R-commander to input and analyze data
• be able to analyze data using simple and multiple regression models as well as logistic regression
• understand the relationship between regression and ANOVA
• understand diagnostics for testing modelling assumptions
• understand methods for model selection
• be able to interpret computer output, and be able to write reports that analyse data and interpret computer output

Pre-requisites

Restrictions

For further information see Mathematics and Statistics.