机器学习和人工智能基础因果推理和建模

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上一讲： 9. Challenge Moderation, mediation, or a third variable

下一讲： 1. Turing, Enigma, and CAPTCHA

视频列表

0 - Introduction
1. Thinking about causality
2. What you should know
1 - Experimental Design and Statistical Controls
1. The investigator, the jury, and the judge
2. Fisher and experiments
3. John Snow and natural experiments
4. Double blind studies
5. Control variables (ANCOVA)
6. Judea Pearl Problems with control variables
7. Moderation, mediation, and lurking variables
8. Simpson's paradox
9. Challenge Moderation, mediation, or a third variable
10. Solution Moderation, mediation, or a third variable
2 - Conditional Probability and Bayes' Theorem
1. Turing, Enigma, and CAPTCHA
2. Enigma and uncertainty
3. Developing an intuition for Bayes with Wordle
4. Wordle and conditional probability
5. Wordle, bans, and bits
6. Wordle and Bayes' theorem
7. Challenge Conditional probability and Bayes' theorem
8. Solution Conditional probability and Bayes' theorem
3 - Prediction and Proof with Bayesian statistics
1. Contrasting frequentist statistics and Bayesian statistics
2. Bayesian T-Test with JASP
3. Google Optimize
4. Bayes and rare events
5. Challenge JASP
6. Solution JASP
4 - Causal Modeling with Structural Equation Modeling (SEM)
1. Sewell Wright
2. Introducing path analysis and SEM
3. SEM example Intention
4. Myths about SEM
5. Latent variables in SEM
6. Finding direction of causality with SEM (PSAT)
5 - Causal Modeling with Bayesian Networks
1. Judea Pearl and the causal revolution
2. Downloading BayesiaLab and resources
3. Introducing BayesiaLab Hair and eye color
4. Introduction to causal modeling with Bayesian networks
5. Bayesian Networks Black Swan case study
6 - Conclusion
1. Taking causality further