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