Causal Inference in Python: Applying Causal Inference in the Tech Industry 1st Edition By Matheus Facure, 9781098140250

“How many clients will an additional dollar of online advertising bring in? Which customers will only buy something if they have a coupon for a discount? How can the optimal pricing strategy be determined? The best way to determine how the levers at our disposal affect the business KPIs we want to alter is through causal inference.

This book’s author, Matheus Facure, a senior data scientist at Nubank, explains the largely untapped potential of causal inference for impact and effect estimates. Managers, data scientists, and business analysts will learn how to use traditional causal inference methods such randomized control trials (A/B testing), linear regression, propensity scores, synthetic controls, and difference-in-differences. For a fundamental example, each technique has an industry application.