Introduction to causal discovery
Causal discovery isn’t a new area. It’s another approach within the umbrella of causal inference that goes beyond mere association to learn the true drivers of observed phenomena. Through the discussions in this chapter, you’ll see that its importance in data analysis lies in its ability to provide actionable insights, inform policy and decision-making, advance scientific understanding, reduce bias, and analyze complex systems. So, let’s go ahead and start peeling back the layers.
Definition and importance
When we talk about causal discovery, we’re trying to understand how things work. We want to figure out what causes what in the world around us, using the data we observe. It’s a method that helps us identify and understand causal relationships from observational data. Its main goal is to uncover direct causal influences, which helps us better grasp the underlying mechanisms behind what we observe. By...
