Module 3, Lecture 1 Headings on slides: • General principles • Data reduction • Assessing multivariate responses

Module 3, Lecture 2 Outline: • Factor analysis • PCA • Case study – beer • Process for interpreting outputs

Module 3, Lecture 3 Outline: • Distance matrices • Transformations and standardisations • Cluster analysis o Types of questions o Carrying it out o Interpreting it

Module 3, Lecture 4 Headings: • Hypothesis testing • nMDS • ANOSIM • SIMPER

Module 3, Lecture 5, Outline (for MANOVA part): • MANOVA o Uses in ecology o Comparison to ANOVA o Process and theory underpinning it o Choosing a test statistic o Corrections for multiple comparisons?

Module 3, Lecture 6 Headings: • Rarefaction • Bayesian approaches • Frequentists vs Bayesians