Statistical Inference

Lecturer: Adam Amara (ETHZ)

Lecture topics.

• 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.