- Course Code
- BI5010
- Credit Points
- 7.5
- Course Coordinator
- Drs David Lusseau, Rene van der Wal and Alex Douglas
Pre-requisites
BI5009 or equivalent
Overview
The module will be divided into themed weeks during which students will gain skills in sampling design (through practicals) and analytical techniques (through lecture and computer labs).
Week 1: introduction to complex study design - students are introduced to nested and repeated sampling and random effects.
Week 2: dealing with complex design in linear models - students learn to account for complex sampling and effects in linear models using linear mixed effect models, generalised least squares models and generalised additive models.
Week 3: correlated data structure - students are introduced to spatial and temporal autocorrelation in lectures and in practicals and learn ways to deal with it in linear models.
Structure
Three 2-hour flexible lecture/tutorial slots each week (thread II)
One eight-hour practical session each week including field trip and computer lab (thread II)
Assessment
The module will be assessed based on an independent report (100%).