C8600 Multivariate Statistical Methods

Faculty of Science
Spring 2002
Extent and Intensity
2/0/0. 4 credit(s). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
Chemistry Section – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D.
Prerequisites
Knowledge on basic unidimensional exploratory statistical techniques, analysis of variance, correlation analysis, simple regression.
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
Basic mathematical procedures with vectors and matrices.
Correlation structure of multidimensional data.
Distribution of multidimensional data - basic tests.
Cluster analysis.
Discrimination analysis.
Logistic regression.
Introduction to ordination methods.
Canonical correlation.
Application of Markov chains.
Estimating species abundance.
Multivariate analysis of variance.
Syllabus
  • Basic mathematical procedures with vectors and matrices. Introduction to mathematical statistics.
  • Correlation structure of multidimensional data. Similarity of parameters and cases (R-mode and Q-mode analysis).
  • Distribution of multidimensional data - basic tests.
  • Cluster analysis. Basic algorithms and finding of optimal metric for analysis. Similarity coefficients.
  • Discrimination analysis - continuous and bivariate data, basic algorithms of discrimination analysis.
  • Logistic regression - comparison with discrimination analysis.
  • Introduction to ordination methods. Multidimensional nominal data. Principal component analysis. Experimental approaches, graphical output. Factor analysis. Correspondence analysis.
  • Canonical correlation. Multivariate processing of species diversity data. Application of Markov chains.
  • Estimating abundance: Mark and recapture techniques, quadrat counts and line transects, distance methods and removal methods.
  • SAR, QSAR, QSAM.
  • Multivariate analysis of variance (MANOVA).
Literature
  • HEBÁK, Petr. Texty k bayesovské statistice. Vyd. 1. Praha: Vysoká škola ekonomická v Praze, 1999, 139 s. ISBN 8070798629. info
  • LEGENDRE, Pierre and Louis LEGENDRE. Numerical ecology. 2nd engl. ed. Amsterdam: Elsevier, 1998, xv, 853 s. ISBN 0-444-89249-4. info
  • Statistické zpracování experimentálních dat :v chonometrii, biometrii, ekonometrii a v dalších oborech přírodních , technických a společenských věd. Edited by Milan Meloun. 2. vyd. Praha: East Publishing, 1998, xxi, 839 s. ISBN 80-7219-003-2. info
  • MELOUN, Milan and Jiří MILITKÝ. Statistické zpracování experimentálních dat : sbírka úloh (s disketou). Vyd. 1. Pardubice: Universita Pardubice, 1996, 308 s. ISBN 8071940755. info
  • MELOUN, Milan and Jiří MILITKÝ. Statistické zpracování experimentálních dat. [1. vyd.]. Praha: Plus, 1994, 839 s. ISBN 80-85297-56-6. info
  • MELOUN, Milan. Statistické zpracování experimentálních dat (v chemometrii, biometrii, ekonometrii a dalších oborech přírodních, technických a společenských věd. 1. vyd. Praha: Plus, 1994, 839 s. : i. ISBN 80-85. info
  • HEBÁK, Petr and Jiří HUSTOPECKÝ. Vícerozměrné statistické metody s aplikacemi. 1. vyd. Praha: SNTL - Nakladatelství technické literatury, 1987, 452 s. URL info
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Spring 2000, Spring 2001.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/sci/spring2002/C8600