The confrontation of theories with data is at the
core of modern sciences. In astrophysics state of the art statistical methods
are used to assess and improve models. In this course you will learn from first
principles the basics of Bayesian statistics. The course aims that you gain an
intuition of which methods to apply in different situations. An important
concept is the role of priors. It is only in comparison to prior knowledge that
data can inform you about a model. In particular we will study the following
topics:
Foundations of Bayesian Statistics
Parameter Estimation - Simple Cases
Parameter Estimation - Advanced Topics
Model Selection
Probabilities
Non-parametric estimation
Design of Experiments
Extensions of Least-Square Methods
Monte Carlo Markov Chain Sampling
The core of the course is not just the lecture. You will learn with hands on
problem sheets to tackle statistical problems with the help of experienced
tutors.
- Docente: Steffen Hagstotz
- Docente: Henrique Rubira
- Docente: Barbara Sartoris
- Docente: Jochen Weller