Causal inference and causal graphical models · Advanced reference manual

Introduction

What this guide covers

Introduction Causal Inference and Graphical Models

Overview

Topics covered

• Introduction
• Causal Inference: Causal Graphical Models
• Introduction to causal inference and causal revolution
• Simpson's paradox from the causal perspective
• The language of Structural Causal Models (SCM)
• Directed Acyclic Graphs (DAGs) and graph terminology

Related concepts

Main connections

• Causal inference & potential outcomes
• Directed acyclic graphs (DAGs)
• Confounding & selection bias
• Conditional probability & independence
• Calculus & differentiation
• Mean & expected value

Compatible notation

Mathematical sample in LaTeX

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