- Course Code
- BI5009
- Credit Points
- 15
- Course Coordinator
- Dr David Lusseau; Dr Rene Van der Wal
Pre-requisites
An undergraduate statistics course.
Overview
The module will be divided in themed weeks during which students will gain skills in sampling design (through practicals) and analytical technique (through lecture and computer labs).
Week 1: introduction to biostatistics
Students are introduced to simple sampling design, core statistical concepts, and statistical software.
Week 2: introduction to statistical modelling
Students continue their progression in statistical analyses and are introduced to complex sampling design.
Week 3: generalised Linear Models
Students learn about generalised linear models and the interpretation of models (model fitting, model selection, and model validation) and are exposed to more advanced models. Students carry out sampling in groups for their report.
Week 4: categorical data
Students learn about statistical technqiues for categorical data. They also learn about power analyses to understand the influence of sample size on tests results.
Week 5: multivariate statistics
Students cover multivariate statistical techniques and are given the opportunity to go over material covered in previous weeks.
Week 6: student-lead teaching
Students are given the opportunity to go over previous material to reinforce learning and are given time to prepare their report.
Structure
Three 3-hour lectures per week. One 8-hour practical session each week including field trip and computer lab.
Assessment
The module will be assessed based on 2 graded practicals (20% each) and an independent report (60%)