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Bayesian, Probability, Causal Analysis
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Module 4
The Language of Causation: SCMs and DAGs
1
Understanding SCMs: Autonomous Causal Mechanisms
Explain the philosophical motivation behind structural causal models (SCMs) as representations of autonomous causal mechanisms.
2
DAGs: Visualizing Causal Assumptions
Interpret directed acyclic graphs (DAGs) as expressions of qualitative causal assumptions, distinct from statistical models.
3
The do-operator and the Philosophy of Causal Inference
Explain the do-operator and why the distinction between P(Y|X) and P(Y|do(X)) is philosophically fundamental to causal inference.
Previous module
From Correlation to Causation: A Philosophical Shift
Next module
Synthesis: Causal Inference and Bayesian Beliefs