516-0055/01 – Computer Processing of Experimental Data (PZED)

Gurantor departmentInstitute of PhysicsCredits3
Subject guarantordoc. Dr. Ing. Michal LesňákSubject version guarantordoc. Dr. Ing. Michal Lesňák
Study levelundergraduate or graduateRequirementCompulsory
Year2Semesterwinter
Study languageCzech
Year of introduction2007/2008Year of cancellation2015/2016
Intended for the facultiesUSPIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
LES66 doc. Dr. Ing. Michal Lesňák
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Graded credit 1+2

Subject aims expressed by acquired skills and competences

Repeat the basic knowledge from secondary school information technology and their expansion Define and characterize the basic principles information technology with sight on processing experimental data Solve the simple exercises processing experimental data

Teaching methods

Seminars

Summary

Předmět Počítačové zpracování experimentálních dat rozšiřuje znalosti studentů při zpracování naměřených dat pomoci počítače. Je zaměřen na matematický a statistický software a studenti se zde seznámí s úvodem do statistiky.

Compulsory literature:

Mathworks Inc.: MATLAB R13 HELP, Mathworks Inc., 2002.

Recommended literature:

Mathworks Inc.: MATLAB R13 HELP, Mathworks Inc., 2002.

Way of continuous check of knowledge in the course of semester

E-learning

Other requirements

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Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Content focus: - Introductory lecture. Repeat the basic concepts: uncertainty, variables, functions. - Statistical analysis of univariate data. Point estimates of parameters of location, dispersion and shape. - Introduction to Matlab - user environment command window, basic commands and functions. - Basic operation of Matlab, typing, using the toolbox, statistical toolbox. - Graphic Data Processing Matlab help. - Presentation of data in Matlab, data from other applications and other applications. - Simple linear regression, regression models, nonlinear regression. - Use of Fourier transform, properties of Fourier transform, fast Fourier transformation (FFT). - The ideal, natural and immediate sampling, Shannon - Kotělnikův theorem. - Introduction to using the program Statigraf. - Individual work, implementation of simple measurements and their processing.

Conditions for subject completion

Full-time form (validity from: 2012/2013 Winter semester, validity until: 2015/2016 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Graded exercises evaluation Graded credit 100 (100) 51 3
        Written exam Written test 30  15 3
        Other task type Other task type 70  21 3
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2015/2016 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2015/2016 (B3942) Nanotechnology (3942R001) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2014/2015 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2013/2014 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2012/2013 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2012/2013 (B3942) Nanotechnology (3942R001) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2011/2012 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2010/2011 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2009/2010 (B3942) Nanotechnology P Czech Ostrava 2 Compulsory study plan
2008/2009 (B3942) Nanotechnology (3942R001) Nanotechnology P Czech Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction



2015/2016 Winter
2011/2012 Winter
2009/2010 Winter