Causal inference

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Related lectures (32)

Page 3 of 4

Developing a Model: Simple Example

Presents a simple example of developing a model with a focus on variables and causal relationships.

Causal Inference: Front Door Criterion

Explains the front door criterion in causal inference and its sufficient conditions for variables blocking paths effectively.

Difference Equations

Covers the concept of difference equations and properties of causal vs. stable systems.

Invariance, Causality, and Robustness

Explores invariance, causality, and robustness in data analysis, addressing challenges and implications for distribution generalization.

Block Diagrams: Causal LTI Systems

Covers block diagrams and causal LTI systems with rational transfer functions.

Statistical Analysis of Networks: Link Prediction and Biclustering

Explores link prediction, logistic regression, causal inference, and biclustering in statistical network analysis.

Assessing Market Regulation

Explores the assessment of market regulation, focusing on high-frequency trading and the impact of regulatory changes on liquidity and market quality.

Statistical Inference for Bandit Data

Explores statistical inference for bandit data, focusing on personalized treatment actions and challenges of standard estimators.

Optimization and Simulation: Introduction to Simulation

Introduces state-of-the-art methods in optimization and simulation, covering topics like statistical analysis, variance reduction, and simulation projects.

Optimization and Simulation

Explores optimization, simulation, data analysis, and the importance of considering more than just the mean in engineering systems.