Welcome to the BEDA Handbook
Introduction
Thank you for joining BIOL202 Biology Experimental Design and Analysis, known to many as BEDA (🐝-da). The ability to critically evaluate evidence is a fundamental life skill, and our aim is to help you build a strong foundation in it by helping you develop essential, hands-on skills in experimental design and analysis. We will move beyond theory and focus on the ‘how’ and ‘why’ of research:
- How do you design a robust study from the ground up?
- Why does your study’s design fundamentally shape its results?
- How do you select the right statistical tools for your specific research question?
The skills you learn will be invaluable not just in biology, but in any future career path you choose.
Importante note: We build upon foundational statistical concepts, so a basic understanding is assumed. If you need a refresher, please see: Am I ready for BEDA?
Using this handbook
This online handbook is your primary resource for BEDA. Use the sidebar to navigate through the content. We will walk you through its structure during our first week. To get started, head over to Unit Information to learn about the course structure, assessments, and what to expect.
Below is a quick schedule of the unit, where you can find links to the lectures and practicals.
Schedule
Module 1: Fundamentals
Week 01 – 4 Aug - 8 Aug
Lectures and Practicals
L01a Tue: Guest lecture
L01b Tue: The nature of data and numbers in biology experiments
L01c Tue: Welcome to BEDA | PDF
L01d Wed: (Re-) introduction to experimental design and analysis | PDF
Practical Week 01: Getting started
Announcements and resources
Week 02 – 11 Aug - 15 Aug
Lectures and Practicals
L02a Tue: What is a representative sample? | PDF
L02b Wed: Modelling fundamentals – a linear model with a single, continuous \(X\) | PDF
L02c Wed: (Almost) every statistical technique is a linear model (or, identifying response and predictors) | PDF
Practical Week 02: Study design
Announcements and resources
Common statistical tests are linear models
Quiz 2 [0%] – opens Friday
Week 03 – 18 Aug - 22 Aug
Lectures and Practicals
L03a Tue: Is my model appropriate? (testing assumptions) | PDF
L03b Wed: Modelling differences between two things: A linear model with a single, categorical (and binary) \(X\) | PDF
Practical Week 03: Data analysis
Announcements and resources
Quiz 3 [0%] – opens Friday
Early Feedback Task [5%] – opens Friday 10am
Week 04 – 25 Aug - 29 Aug
Lectures and Practicals
L04a Tue: Modelling multiple relationships: a linear model with multiple, continuous \(X\) variables | PDF
L04b Wed: Modelling multiple differences: a linear model with two or more categorical \(X\) variables | PDF
L04c Wed: Model transformations – why, and how? | PDF
Practical Week 04: Check timeline
Announcements and resources
Evaluation Quiz (10%)
More information on the Evaluation Quiz
Week 05 – 1 Sep - 5 Sep
Lectures and Practicals
L05a Tue: Control, fixed and random variables – adding sense to models (ANCOVA and mixed models) | PDF
L05b Wed: You’ve got this – Module 1 revision | PDF
Practical Week 05: Check timeline
Announcements and resources
Work on your experiments
Module 2: Univariate experiments
Week 06 – 8 Sep - 12 Sep No practicals this week
Lectures and Practicals
L06a Tue: General refresher
L06b Wed: Is aerobic enzyme activity greater in male or female birds? Dealing with class explanatory variables
No practicals
Announcements and resources
–
Week 07 – 15 Sep - 19 Sep
Lectures and Practicals
L07a Tue: Does wind reduce tree growth? Detecting differences versus describing relationships
L07b Wed: What are the chances of finding a bandicoot? Dealing with binary response data
Practical Week 07: Check timeline
Announcements and resources
–
Week 08 – 22 Sep - 26 Sep
Lectures and Practicals
L08a Tue: Information-theoretic methods vs. null hypothesis testing
L08b Wed: Revision: answering your queries
Practical Week 08: Check timeline
Announcements and resources
–
Mid-semester break
Module 3: Multivariate experiments
Week 09 – 6 Oct - 10 Oct
Lectures and Practicals
L09a Tue: Introduction to multivariate analysis
L09b Wed: Principal Component Analysis (PCA) and Factor Analysis (FA)
Practical Week 09: Week 9
Announcements and resources
Report 1 (25%)
Week 10 – 13 Oct - 17 Oct
Lectures and Practicals
L10a Tue: Clustering
L10b Wed: Non-metric multi-dimensional scaling (nMDS) and hypothesis testing
Practical Week 10: Week 10
Announcements and resources
Informal presentations
Week 11 – 20 Oct - 24 Oct
Lectures and Practicals
L11a Tue: Multivariate analysis of variance (MANOVA)
L11b Wed: Multivariate Revision 1 (no slides)
Practical Week 11: Week 11
Announcements and resources
Group dataset submission (5%)
Week 12 – 27 Oct - 31 Oct
Lectures and Practicals
L12a Tue: Rarefaction and Bayesian analysis
L12b Wed: Multivariate Revision 2 (no slides)
Practical Week 12: Week 12
Announcements and resources
–
Week 13 – 3 Nov - 7 Nov
Lectures and Practicals
Revision and Q&A
Practical Week 13: Feedback, Exam and Discussions
Announcements and resources
Report 2 (15%)