Causal Effects | An introduction

🤝 Your engineers use Claude but sales, ops and finance don't? I fix that for 50 to 200-person software companies: https://aibuilder.academy/yt/BOPOX_mTS0g This is the first video in a series on causal effects. Here I introduce the Potential Outcomes Framework and use it to formulate 3 different types of causal effects. In future videos, I discuss how to compute causal effects from observational data. Series Playlist:    • Causality   📰 Read more: https://medium.com/towards-data-scien... Resources: An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies by Peter C. Austin Counterfactuals and Causal Inference: Methods and Principles for Social Research by Stephen L. Morgan & Christopher Winship An Introduction to Causal Inference by Judea Pearl Introduction - 0:00 Causal Effects - 0:24 3 Types of Variables - 1:01 Potential Outcomes Framework - 1:50 3 Types of Causal Effects - 2:28 1) Individual Treatment Effect (ITE) - 2:38 2) Average Treatment Effect (ATE) - 4:01 2.1) ATE in RCTs - 5:24 3) Average Treatment Effect of Treated/Controls (ATT/ATC) - 6:56 Practical Questions - 9:07