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Course, academic year 2023/2024
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Practical aspects of experimental data treatment - NBCM158
Title: Praktické aspekty zpracování experimentálních dat
Guaranteed by: Department of Chemical Physics and Optics (32-KCHFO)
Faculty: Faculty of Mathematics and Physics
Actual: from 2020
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:1/1, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: Mgr. Jan Alster, Ph.D.
RNDr. Vladimír Kopecký, Ph.D.
Annotation -
Lecture gives introduction to basic data processing methods using real world datasets typical for chemical physics and biophysics as an example. Some common mistakes and problems of data processing are pointed out.
Last update: Procházka Marek, prof. RNDr., Ph.D. (28.01.2019)
Course completion requirements -

Course is completed by passing examination consisting of commented analysis of assigned dataset and analysis output. Knowledge and proper utilization of methods introduced in the lecture will be evaluated.

Last update: Procházka Marek, prof. RNDr., Ph.D. (04.05.2020)
Literature -

Jiří Englich, Úvod do praktické fyziky I, MATFYZPRESS, Praha 2006, ISBN 80-86732-93-2

Herman P., Lee J.C. (2012) The Advantage of Global Fitting of Data Involving Complex Linked Reactions. In: Fenton A. (eds) Allostery. Methods in Molecular Biology (Methods and Protocols), vol 796. Springer, New York, NY

Thomas J. DiCiccio and Bradley Efron, Bootstrap Confidence Intervals, Statistical Science, 1996, Vol. 11, No. 3, 189-228

Katharine Megan Mullen,Separable nonlinear models: theory, implementation and applications in physics and chemistry, Vrije Universiteit Amsterdam 2008, ISBN 978-90-8659258-6

Last update: Procházka Marek, prof. RNDr., Ph.D. (30.04.2019)
Syllabus -

Basics of Python, Matlab and R

Loading, storing and displaying data

Simple processing (artefact removal, averaging, interpolation, smoothing)

Fourier transformation (filtering, interpolation)

Fitting (selection of suitable method, determination of parameter uncertainties and correlations, model testing, implementation)

Determination of peak position, width and shape (laser pulse duration measured using two pulse cross-correlation, energy levels in absorption spectra, factorization of Raman spectra)

Single-curve and global analysis (determination of lifetimes from time evolution of triple-minus-singlet spectra, analysis of reaction kinetics of allosteric enzyme)

Selected complex problems (e.g. determination of thermodynamic parameters or equilibrium constants from series of Raman spectra: background removal, SVD, model fitting, model testing)

Last update: Procházka Marek, prof. RNDr., Ph.D. (28.01.2019)
 
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