FU:TFNPV0004 Data Processing and Interpret. - Course Information
TFNPV0004 Data Processing and Interpretation
Institute of physics in Opavasummer 2025
- 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 - 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
- Particle physics (programme FU, TFYZNM)
- Computer physics (programme FU, TFYZNM)
- Relativistic astrophysics (programme FU, TFYZNM)
- 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 taught: every week.
- Enrolment Statistics (summer 2025, recent)
- Permalink: https://is.slu.cz/course/fu/summer2025/TFNPV0004