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Instructors: Dr. Michael Distler
Event type:
Lecture/practice class
Displayed in timetable as:
08.128.730
Hours per week:
4
Credits:
6,0
Language of instruction:
Englisch
Min. | Max. participants:
- | -
Contents:
- Statistics: probability, distributions, special discreet distributions, important probability density functions, theorems, sampling, multidimensional distributions, covariance matrix
- Uncertainties, systematic uncertainties, error propagation, confidence intervals
- Monte Carlo methods: random number generators, Monte Carlo integration
- Parameter estimation: maximum likelihood method, method of least squares
- Hypothesis testing
- Unfolding, factor analysis
- Introduction to Bayesian statistics
Recommended reading list:
- V. Blobel, E. Lohrmann: Statistische und numerische Methoden der Datenanalyse, Teubner Verlag (1998)
- S. Brandt: Datenanalyse, BI Wissenschaftsverlag (1999)
- Philip R. Bevington: Data Reduction and Error Analysis for the Physical Sciences, McGraw-Hill (1969)
- R.J. Barlow: Statistics, John Wiley & Sons (1993)
- G. Cowan: Statistical Data Analysis, Oxford University Press (1998)
- G. Bohm, G. Zech: Introduction to Statistics and Data Analysis for Physicists, Verlag Deutsches Elektronen-Synchrotron (available online)
- W.T. Eadie et al.: Statistical Methods in Experimental Physics, North Holland Publishing Company
- Donald E. Knuth: The Art of Computer Programming, Addison-Wesley (1998)
- William H. Press et al.: Numerical recipes in C, Cambridge University Press (1992)
- William M. Bolstad et al.: Introduction to Bayesian Statistics, John Wiley & Sons (2017)
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