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Causality, Decision Making and Data Science

stanford-causal-inference-class.github.io · 312 words · saved by 1 readers

Home Syllabus Summary Materials Course Materials Lecture Slides Lecture 1 – Introduction and Statistics Refresher Lecture 2 – Causality and Correlation Lecture 3 – The Magic of Randomized Control Trials Lecture 4 – Problems with Experiments Lecture 5 – Online Experiments Lecture 6 – Friedman's Permanent Income Hypothesis Lecture 7 – Regression! (Motivated by Understanding the Effect of UBI) Lecture 8 – Empirical Evidence on the Effect of Unearned Income Lecture 9 – Heterogeneous Treatment Effects and Random Forests Lecture 10 – Returns to Education (Some Theory and Some Regressions) Lecture 11 – Instrumental Variables (And the Effect of Military Service) Lecture 12 – The Return of Instrumental Variables Pre-Class Prompts All Pre-Class Prompts Starting From Lecture 3 Assignments Assignment 0 - Statistics Refresher Assignment 1: Randomized Experiments 📓 Download Notebook ☁️ Open in Google Colab 📊 Download Dataset Assignment 2: Universal Basic Income 📓 Download Notebook ☁️ Open in Goog

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