Course: Experimental Data Analysis

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Course title Experimental Data Analysis
Course code KMI/AED
Organizational form of instruction Lecture + Lesson
Level of course Master
Year of study not specified
Semester Winter and summer
Number of ECTS credits 6
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Křemenáková Dana, doc. Dr. Ing.
  • Salačová Jana, Ing. Ph.D.
  • Militký Jiří, prof. Ing. CSc.
Course content
1.Multivariate data. 2.Exploratory analysis of multivariate data. 3.Principal components anylysis. 4.Basic statistical characteristics of multivariate data 5.Construction of multivariate data distribution characteristics. 6.Confirmatory analysis of multivariate data 7.Cluster analysis. 8.Basic concepts of regression. 9.Linear regression model. 10.Basic of LSM.

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing), Dialogue metods(conversation,discussion,brainstorming)
  • Class attendance - 56 hours per semester
  • Home preparation for classes - 28 hours per semester
Learning outcomes
The main aim is description of selected methods for statistical analysis of multivariate data by using of exploratiry and graphically oriented tools. The selected techniques of multivariate regression models building will be presented. The system MATLAB will be used as prototype for creation of basic algorithms and computation.
Enhancing knowledge in exploratory analysis of multivariate data, focus on evaluation of multivariate data analysis of significance or nonsignificance phenomena for population and sample data, important statistical models for linearity and nonlinearity.
Prerequisites
Knowledge of basic statistical methods for univariate data, probability theory for univariate data, least squares method, the basic mathematical tools for investigation of functions and data fitting functions, integrals, derivatives, combinations, matrices, knowledge of programming in Matlab or other statistical software

Assessment methods and criteria
Written exam

Credit: elaboration of semestral works, successfully passed tests Exam: written
Recommended literature
  • Meloun M., Militký J., Hill M. Počítačová analýza vícerozměrných dat v příkladech. Academia Praha, 2005.
  • Meloun M., Militký J., Forina, M. Chemometrics for Analytical. Chemistry, P Aided Regression vol.2. Ellis Horwood, London, 1994.
  • Meloun M., Militký J., Forina, M. Chemometrics for Analytical. Chemistry. Statistical Data Analysis Vol.1. Ellis Horwood, London, 1992.
  • Meloun M., Militký J. Statistická analýza experimentálních dat. Praha : Academia, 2004. ISBN 80-200-1254-0.
  • Meloun, M., Militký, J. Statistické zpracování experimentálních dat. Ars Magna, Praha 1998.
  • Ryan T.P. Statistical Methods for Quality Improvement, J.Wiley New York 1989.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Engineering (ANG) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Quality Control (2012) Category: Special and interdisciplinary fields 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Nonwoven and Nanomaterials (ANG) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Nonwoven and Nanomaterials (2012) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Engineering (2012) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Engineering (2018) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Technology (2012) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Quality Control (12) Category: Special and interdisciplinary fields 2 Recommended year of study:2, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Technology (2012) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Technology (2012) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Engineering (2012) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter
Faculty: Faculty of Textile Engineering Study plan (Version): Clothing and Textile Engineering (2018) Category: Textile production and clothing industry 1 Recommended year of study:1, Recommended semester: Winter