UFDF047 Observational data processing

Faculty of Philosophy and Science in Opava
Summer 2022
Extent and Intensity
0/0/0. 0 credit(s). Type of Completion: dzk.
Guaranteed by
doc. RNDr. Gabriel Török, Ph.D.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava
Prerequisites
There is no explicit assumption of having previously undertaken other courses related to the subject matter. The course is primarily aimed to provide support for current bachelor and master theses involved with observational themes. Students are recommended to contact their lector/adviser prior to their inscription to the course.
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 course offers an overview of fundamental aspects in the field of observational data analysis with particular focus on regression analysis. Students are coached to solve problems that involve evaluation of experimentally obtained relations of functions of one or more variables. They are provided with theoretical and practical background for data modeling - linear and nonlinear regression, searching for extrema and roots of obtained relations, and statistical matching of predicted and measured function relations and distributions. Special attention is paid to practical applications of algorithms and to studying both their direct interpretation (e.g. in C++) and the possibility of high-level programming languages dealing with data processing (IDL), possibly also in relation to software for algebraic manipulations (Maple, Mathematica).
Literature
    recommended literature
  • M. Javůrek, I. Taufer. Nebojme se nelineární regrese. CHEMagazín, 2006. info
  • Kvasnica, J. Matematický aparát fyziky. Academia, 2004. ISBN 80-200-0603-6. info
  • Brandt, Siegmund. Data analysis: statistical and computational methods for scientists and engineers. New York, Springer-Verlag, 1998. ISBN 0-387-98498-4. info
  • William H. Press, Saul A. Teukolsky, William T. Vetterling, and. Numerical Recipes with Source Code CD-ROM 3rd Edition: The Art of Scientific Computing. Cambridge University Press, 1997. info
  • Z. Riečanová a kol. Numerické metody a matematická štatistika. Alfa, Bratislava, 1987. ISBN 063-559-87. info
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Teacher's information
* semestral project
* presentation in front of the group -€ topic assigned by the lecturer
The course is also listed under the following terms Winter 2013, Summer 2014, Winter 2014, Summer 2015, Winter 2015, Summer 2016, Winter 2016, Summer 2017, Winter 2017, Summer 2018, Winter 2018, Summer 2019, Winter 2019, Summer 2020, Winter 2020, Summer 2021, Winter 2021.
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