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Instructors: Prof. Dr. Jens Erler
Event type:
Lecture/practice class
Displayed in timetable as:
Hours per week:
4
Credits:
6,0
Language of instruction:
Englisch
Min. | Max. participants:
- | -
Requirements / organisational issues:
No prior knowledge in probability theory and statistics is assumed.
Contents:
The following topics will be covered:
1) Probability Theory
2) Bayesian Inference
3) Multivariate Statistics
4) Posterior Approximation
5) Regression Analysis
6) Nonlinear and Nonparametric Models
Recommended reading list:
A. Gelman, J.B. Carlin, H.S. Stern, D.B.Dunson, A. Vehtari, D.B. Rubin, Bayesian Data Analysis (Chapman and Hall/CRC, 2013)
Additional information:
The theoretical background of data analysis and statistics will be introduced.
Emphasis will be on applications and many examples will be discussed.
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