Practical statistics for physics and astrophysics  

Nontrivial data analysis problems are frequently encountered in modern astronomy, cosmology and physics. They require an understanding of statistical methods, practical skills with software tools and sometimes some ingenuity that comes with experience. The student will gain a practical knowledge of statistical methods and software as applied to many example problems. Basic probability theory will be covered before learning about Bayesian and frequentist inference problems, Monte Carlo techniques, Fisher matrices, parameter estimation, non-parametric tests, hypothesis testing, and supervised and unsupervised classification and regression problems. The student will become familiar with current software in Python for analysing data and fitting models while getting an understanding of the theory behind them.
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English
Practical statistics for physics and astrophysics
English

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or HaDEA. Neither the European Union nor the granting authority can be held responsible for them. The statements made herein do not necessarily have the consent or agreement of the ASTRAIOS Consortium. These represent the opinion and findings of the author(s).