Causal Inference and Discovery in Python

4

Graphical Models

Welcome to Chapter 4!

So far, we have used graphs mainly to visualize our models. In this chapter, we’ll see that from the causal point of view, graphs are much more than just a visualization tool. We’ll start with a general refresher on graphs and basic graph theory. Next, we’ll discuss the idea of graphical models and the role of directed acyclic graphs (DAGs) in causality. Finally, we’ll look at how to talk about causality beyond DAGs. By the end of this chapter, you should have a solid understanding of what graphs are and how they relate to causal inference and discovery.

This knowledge will give us the foundations to understand Chapter 5. This and the next chapter are critical to understanding the very essence of causal ...