Principal Coordinates Analysis (PCoA) is a flexible technique for working with multiple variables and observations. By working with a distance or dissimilarity matrix, PCoA can be applied to quantitative variables, qualitative variables, or even a mix of both. Consequently, PCoA is a great tool to simplify, visualize, and understand relationships among observations. Through PCoA, you will be able to
- work with an array of dissimilarity measures,
- reduce the dimensionality of your data,
- identify and visualize relationships and structure among your observations.
In this workshop, you will learn to apply and interpret PCoA and leave equipped with the tools needed to conduct and use PCoA. We will illustrate methods by exploring several datasets using R.