Causality and a fundamental issue

The goal in this chapter is to clarify and simplify concepts that, though they may seem clear and straightforward in daily conversation, reveal a layer of complexity when expressed mathematically. Our approach is informed by the Neyman-Rubin causal model [1], often referred to as the potential outcomes framework. This framework is not just an academic exercise but also a practical tool to understand how specific actions lead to real-world outcomes.

Imagine you live in a loud/noisy neighborhood and consider moving to a quieter one so you can better focus on your studies. The key question is: does moving to a quieter place actually cause an increase in your concentration?

Consider this: you move and find your concentration improves. But it’s important to question whether this improvement might have happened even if you hadn’t moved. If the answer is yes, then the move itself might not be the main reason for your better focus, challenging...