Linear models and regression: - Linear regression - Nonlinear regression - Logistic and Poisson regression - Generalised linear models Graphical Models and Causality: - Conditional independence statements - Hammersley-Clifford theorem - Gibbs sampling - Bayesian networks - Causal inference - Markov random fields - Graphical and hierarchical models - Applications
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