BEDA Handbook
Welcome to the BEDA handbook. This book contains (most) lectures, tutorials and practical content for BIOL2022. Unless otherwise noted, material published here is available under the CC BY 4.0 licence. See About this handbook for the licence scope, exclusions, edition and citation details.
PDF handbook The PDF version will be available soon.
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| Week | Lectures | Practical | Notes |
|---|---|---|---|
| 1 | Introduction and fundamentals Welcome to BEDA! | Open |
|
| 2 | Sampling and the linear model Randomisation and why we teach the linear model first | Open |
|
| 3 | Choosing the right model(s) The easy way to validate model assumptions. | Practical session |
|
| 4 | Multiple predictors and transformations Expanding models and transformations to increase model fit. | Practical session |
|
| 5 | Controls and revision How to control your experiments with data that you collect. | Practical session |
|
| 6 | Refresher and categorical variables A refresher on designing experiments with categorical variables. | No practical | — |
| 7 | Relationships and binary responses How to design experiments with continuous or binary responses. | Practical session | — |
| 8 | Model selection and revision Which model should we use? Some ideas. | Practical session |
|
| Break | Mid-semester break — 28 September–2 October 2026 | ||
| 9 | Multivariate analysis and PCA Introducing multivariate analysis, principal component analysis and factor analysis. | Practical session |
|
| 10 | Clustering and multidimensional scaling Using clustering and nMDS to identify and test multivariate patterns. | Practical session |
|
| 11 | MANOVA and multivariate revision The MANOVA way of designing and interpreting experiments. | Practical session |
|
| 12 | Rarefaction and Bayesian analysis The lectures cover rarefaction for diversity comparisons and Bayesian statistical inference. | Practical session | — |
| 13 | Exam revision You will review the course's experimental-design and modelling concepts for the final exam. | Practical session |
|
Weekly schedule
Lectures Welcome to BEDA!
Practical Open
- Resource: Am I ready for BEDA?
- Practice quiz (0%): Quiz 1
- Notice: Snail-collecting competition: prizes to be won
Lectures Randomisation and why we teach the linear model first
Practical Open
- Resource: Common statistical tests are linear models
- Practice quiz (0%): Quiz 2
Choosing the right model(s)
Lectures The easy way to validate model assumptions.
Practical
- Practice quiz (0%): Quiz 3
- Notice: Early Feedback Task opens Friday 21 August at 10:00
Multiple predictors and transformations
Lectures Expanding models and transformations to increase model fit.
Practical
- Assessment (5%): Early Feedback Task due Friday 28 August at 23:59
Controls and revision
Lectures How to control your experiments with data that you collect.
Practical
- Assessment (10%): Evaluation Quiz due Friday 4 September at 23:59
- Notice: Begin working on Report 1
Refresher and categorical variables
Lectures A refresher on designing experiments with categorical variables.
Practical No practical
Notes —
Relationships and binary responses
Lectures How to design experiments with continuous or binary responses.
Practical
Notes —
Model selection and revision
Lectures Which model should we use? Some ideas.
Practical
- Assessment (25%): Report 1 due Friday 25 September at 23:59
Mid-semester break — 28 September–2 October 2026
Multivariate analysis and PCA
Lectures Introducing multivariate analysis, principal component analysis and factor analysis.
Practical
- Notice: Labour Day — Monday 5 October
Clustering and multidimensional scaling
Lectures Using clustering and nMDS to identify and test multivariate patterns.
Practical
- Notice: Present your experimental design for feedback
- Notice: Prepare for Report 2
MANOVA and multivariate revision
Lectures The MANOVA way of designing and interpreting experiments.
Practical
- Assessment (5%): Report 2 group dataset due at 10:00 on your practical day
Rarefaction and Bayesian analysis
Lectures The lectures cover rarefaction for diversity comparisons and Bayesian statistical inference.
Practical
Notes —
Exam revision
Lectures You will review the course’s experimental-design and modelling concepts for the final exam.
Practical
- Assessment (15%): Report 2 individual report due Friday 6 November at 23:59