Concept

Rubin causal model

Related lectures (31)

Explores reliable broadcast algorithms, focusing on causal order and uniform reliability, with exercises on failure detector properties and memory optimization.

Statistical Analysis of Networks: Link Prediction and Biclustering

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

Causal Inference in Epidemiology: Pregnancy and Prostate Cancer

Explores causal inference in epidemiology, focusing on COVID-19's impact on preterm birth and refining treatment strategies for prostate cancer.

Causal Inference: Understanding Treatment Effects

Explores treatment effects, confounding variables, and challenges in interpreting observational study results.

Causality and Invariant Machine Learning

Explores causality, correlation, and spurious correlations in machine learning, emphasizing bias mitigation and invariance across environments.

Total Order Broadcast: Consensus Transformation

Explores causal and total order broadcast in distributed algorithms, including exercises on total-order property and consensus transformation.

Causal Inference: Learning Graph Structures

Explores causal inference through learning graph structures for causal reasoning from observational data.

Birth Month Impact on Athlete Success

Investigates how birth month influences athlete success, analyzing Japanese athletes' dataset to explore trends in birthdates and occupations.

Direct LiNGAM Algorithm

Covers the Direct LiNGAM Algorithm, focusing on causal order estimation and residual minimization.

Instrumental Variables: Part 1

Introduces instrumental variables to address endogeneity issues, using examples to illustrate practical applications and testing requirements.

Region of Convergence: Single Pole

Covers the concept of Region of Convergence for signals with single poles.