Lecturer: Adam Amara (ETHZ)
- Probabilities: Joint, conditional and marginal -> on the road to Bayes Theorem.
- Dealing with full probability density functions in the case where a likelihood can be written -> grids, adaptive grids and MCMC.
- Linear models with Gaussian errors -> Generalised least square or regressions.
- Understanding the Chi^2 distribution and what it can tell you about your data.