We will now dive into multivariate statistics, a tool set that will allow us to address questions requiring the simultaneous observation or analysis of more than one outcome variable.
We will explore certain methods, such as:
Association (or dis-similarity) measures and matrices;
Classification (or cluster) analysis;
Constrained (or canonical) ordination (in Workshop 10).
Before everything, we will do a little review on matrix algebra.