Causality: An Introduction | How (naive) statistics can fail us
🤝 Want your team maximizing Claude? I run 1:1 and team AI workshops for companies doing $1M+ per year: https://aibuilder.academy/yt/WqASiuM4a-A The first video in a 3-part series on causality. This series is based on the work of Judea Pearl, who laid much of the groundwork for this "new science of cause and effect". Future posts will look more closely at two fields of causality: causal inference and causal discovery. Series Playlist: • Causality 📰 Read more: https://medium.com/towards-data-scien... Resources: The Book of Why by Judea Pearl: https://www.amazon.com/Book-Why-Scien... Spurious Correlation Examples: https://tylervigen.com/spurious-corre... Introduction - 0:00 Why? - 0:50 3 Traps of Statistics - 1:35 Trap 1: Spurious Correlation - 1:42 Trap 2: Simpson's Paradox - 2:34 Trap 3: Symmetry - 4:09 Defining Causality - 5:32 Representing Causality - 6:24 Closing remarks - 8:01
Causal Inference | Answering causal questions
Correlation vs Causation Explained: Why Patterns Can Mislead Us
Causal Discovery | Inferring causality from observational data
The danger of mixing up causality and correlation: Ionica Smeets at TEDxDelft
Judea Pearl: Do(x) Operator and Do-Calculus | AI Podcast Clips
What are degrees of freedom?!? Seriously.
Causal Effects via Propensity Scores | Introduction & Python Code
Judea Pearl: Correlation and Causation | AI Podcast Clips
Causality: What is Causality?
Bayesian Causal inference: why you should be excited
The fragile foundation of inferential statistics
6. Monte Carlo Simulation
An introduction to Causal Inference with Python – making accurate estimates of cause and effect from
Systems Thinking: Causal Loop Diagrams
What is causal inference, and why should data scientists know? by Ludvig Hult
Regression and Matching | Causal Inference in Data Science Part 1
20 Causality
Causal Effects via the Do-operator | Overview & Example
Keynote: The Mathematics of Causal Inference: with Reflections on Machine Learning
