Semester Two 2012
To provide a practical introduction to the fundamentals of linear regression modelling, with emphasis on application to real data and problems.
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 knowledge-base. 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.
• 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
STAT101 or STAT111 or STAT112 or STAT131
This course is co-coded with STAT202. Students must register for tutorial sessions which commence on the second Monday of the course. There is a direct link from your personal Learn page for the course to the student entry point for My Timetable that enables you to self-allocate into one of three lab streams.
Examination and Formal Tests
06 Nov 2012
This course will not be offered if fewer than 5 people apply to enrol.
For further information see
School of Forestry.
All FORE224 Occurrences
Semester Two 2012