Experimental Design and Analyses

In this section
Experimental Design and Analyses
Course Code
BI5009
Credit Points
15
Course Coordinator
Dr David Lusseau; Dr Rene Van der Wal

Pre-requisites

An undergraduate statistics course.

Notes

BI5509 is the code for students starting their programme in January.

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 techniques 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%)