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Lecturer(s)
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Kvita Jiří, Mgr. Ph.D.
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Černý Karel, RNDr. Ph.D.
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Course content
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1. Random variables, probability density distribution, Monte Carlo methods. 2. Maximum likelihood principle, parameters estimation. 3. Curve fitting, chi2 test, correlations, covariance matrix. 4. Limits settings, statistical tests. 5. Multivariate techniques, signal and background separation. 6. Unfolding (deconvolution).
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Learning activities and teaching methods
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Monologic Lecture(Interpretation, Training)
- Homework for Teaching
- 20 hours per semester
- Preparation for the Exam
- 44 hours per semester
- Attendace
- 26 hours per semester
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Learning outcomes
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The aim is to provide students with basic statistical approaches and methods in data analysis in high energy physics.
Demonstrate the understanding and ability to apply basic statistical tools to dealing with graphs, histograms and multidimensional data structures.
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Prerequisites
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Not specified.
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Assessment methods and criteria
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Mark
Class attendance. Knowledge of the course topics, ability to discuss about the course topics in wider contexts.
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Recommended literature
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http://www-library.desy.de/preparch/books/vstatmp_engl.pdf.
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Bohm, G.; Zech, G. Introduction to Statistics and Data Analysis for Physicists.
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Cowan, G. Statistical Data Analysis.
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James, F. Statistical Methods in Experimental Physics.
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