TFNPV0004 Data Processing and Interpretation

Institute of physics in Opava
summer 2023
Extent and Intensity
1/3/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
RNDr. Kateřina Klimovičová, Ph.D. (lecturer)
doc. RNDr. Gabriel Török, Ph.D. (lecturer)
RNDr. Kateřina Klimovičová, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Gabriel Török, Ph.D.
Institute of physics in Opava
Timetable
Mon 12:15–13:00 LPS
  • Timetable of Seminar Groups:
TFNPV0004/01: Mon 13:05–15:30 LPS, K. Klimovičová
Prerequisites (in Czech)
(FAKULTA(FU) && TYP_STUDIA(N))
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 subject acquaints students with fundamentals of scientific data acquisition, processing and interpretation.
Learning outcomes
Upon successful completion of the course, the student will:
- be able to acquire, process and interpret scientific data,
- master key tools for scientific data processing,
- master methods and tools for scientific data modelling, being essentials parts to scientific data interpretation
Syllabus
  • Main topics of the subject:
  • - Acquisition of scientific data and fundamentals of their use
  • - Statistical metods for data processing, probability, random numbers
  • - Distributions, hypothesis testing
  • - Interpolation and extrapolation of data
  • - Data modeling, minimization, linear and nonlinear functions
  • - Least squares method and other regression metods
  • - Graphical presentation of scientific data
  • - Computer tools for large data analysis
  • - Fourier analysis and its application
Literature
    recommended literature
  • Siegmund, B. Data analysis: statistical and computational methods for scientists and engineers, New York: Springer- Verlag, 1998
  • Hasík, K. Numerické metody, skriptum MU SU Opava
  • Fanning, D. W. IDL Programming Techniques, 2nd Edition, NumPy Beginners Guide SciPy
  • Press, W. H., Teukolsky, S. A., Vetterling, W. T., Flannery, B. P. Numerical Recipes with Source Code CD-ROM 3rd Edition: The Art of Scientific Computing, Cambridge University Press, 1997
  • Bartsch, H. J. Matematické vzorce, Academia, 2009
Teaching methods
lecture and discussion, exercises
Assessment methods
oral exam, defense of the project
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms summer 2021, summer 2022, summer 2024.
  • Enrolment Statistics (summer 2023, recent)
  • Permalink: https://is.slu.cz/course/fu/summer2023/TFNPV0004