ENGG 199.19 - Principles of Causality

Description

Helmets increase head injuries. The fastest people are the latest. Hospital patients are less likely to have cancer when their bones are broken. But don’t throw out your helmet, break your leg, or invest in transportation inefficiency just yet... Causality is the beacon of science and foundation of policy, but causal relationships can be lost in a labyrinth of correlation. Instead of caveating correlative studies, this course establishes the principles on which scientists and engineers can answer true causal questions. At the core of this pursuit is experimentation. We will build a formal understanding of randomized control trials that allows us to generalize these principles to observational (i.e. non-experimental) data. These generalizations will give rise to mathematical tools for learning (causal or non-causal) relationships when experiments aren’t quite what we would want them to be.

Prerequisites

ENGS 20 or COSC 10, and ENGS 27 or ENGS 93; or instructor permission.

Notes

All coding assignments will use Python. No previous experience with Python is required.