F7270 Mathematical methods for numerical data analysis

Faculty of Science
Autumn 2011 - acreditation

The information about the term Autumn 2011 - acreditation is not made public

Extent and Intensity
2/1/0. 4 credit(s) (plus extra credits for completion). Type of Completion: graded credit.
Teacher(s)
prof. RNDr. Josef Humlíček, CSc. (lecturer)
Mgr. Vlastimil Křápek, Ph.D. (seminar tutor)
Mgr. Přemysl Maršík, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Josef Humlíček, CSc.
Department of Condensed Matter Physics – Physics Section – Faculty of Science
Contact Person: prof. RNDr. Josef Humlíček, CSc.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The goal of this course is to provide the students with the ability to
- list and explain basic procedures in the probability theory
- apply the knowledge in the case of experimental data treatment, particularly in scope of stating and testing the hypotheses.
Syllabus
  • Probability, random variables. Random vector, statistical dependence. Central limit theorem. Multidimensional normal distribution. Standard probability distributions and their relationships. Statistical estimates, maximum likelihood, least squares. Position of an unknown symmetrical distribution. Linear model for multiple unknowns. Nonlinear model, numerical minimization. Statistical tests. Pearson and Kolmogorov method.
Literature
  • BRANDT, Siegmund. Data analysis : statistical and computational methods for scientists and engineers. Translated by Glen Cowan. 3rd ed. New York: Springer-Verlag, 1998, xxxiv, 652. ISBN 0387984984. info
  • HUMLÍČEK, Josef. Statistické zpracování výsledků měření. 1. vyd. Brno: Rektorát UJEP, 1984, 101 s. info
  • EADIE, W. T. Statističeskije metody v eksperimental'noj fizike. Moskva: Atomizdat, 1976, 334 s. info
Teaching methods
lectures, seminars
Assessment methods
Final project evaluating computer-generated data: estimates, identification of outliers, testing data dstribution, evaluation of indirect measurements, statistical dependence of retrieved parameters.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Autumn 1999, Autumn 2010 - only for the accreditation, Autumn 2000, Autumn 2001, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, spring 2012 - acreditation, Autumn 2012, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.