Causal Inference and Discovery in Python

3

Regression, Observations, and Interventions

In this chapter, we’re going to build a link between associations, interventions, and regression models. We’ll look into the logic of statistical control – a tool used by scientists in the hopes of making their models more robust. Finally, we’ll look into the connection between regression and structural models.

By the end of this chapter, you should have a solid understanding of statistical control and how it can help in estimating causal effects from observational data. This knowledge will allow us to build the more complex non-linear models introduced in Part 2, Causal Inference.

In this chapter, we’ll cover the following topics:

• Associations in observational data versus linear regression
• Causal ...