PřF:Bi8600 Multivariate Statistical Meth. - Course Information

Bi8600 Multivariate Statistical Methods

Extent and Intensity

2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).

Teacher(s)

prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Danka Haruštiaková, Ph.D. (lecturer)
RNDr. Eva Gelnarová (assistant)

Guaranteed by

prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D.

Timetable of Seminar Groups

Bi8600/1: No timetable has been entered into IS.
Bi8600/2: No timetable has been entered into IS.

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

• Ecotoxicology (programme PřF, M-BI)

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

• MELOUN, Milan and Jiří MILITKÝ. Statistické zpracování experimentálních dat. [1. vyd.]. Praha: Plus, 1994, 839 s. ISBN 80-85297-56-6. 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
• HEBÁK, Petr and Jiří HUSTOPECKÝ. Vícerozměrné statistické metody s aplikacemi. 1. vyd. Praha: SNTL - Nakladatelství technické literatury, 1987, 452 s. URL info
• B. Flury and H. Riedwyl (1988) Multivariate statistics. A practical approach. Chapman and Hall, London.
• LEGENDRE, Pierre and Louis LEGENDRE. Numerical ecology. 2nd engl. ed. Amsterdam: Elsevier, 1998, xv, 853 s. ISBN 0-444-89249-4. info
• J. H. Zar (1984). Biostatistical analysis. Prentice Hall. New Jersey.
• G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
• HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
• J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.

Language of instruction

Czech

Further Comments

The course is taught annually.

Teacher's information

http://www.cba.muni.cz/vyuka/

• Enrolment Statistics (Spring 2006, recent)
  
• Permalink: https://is.muni.cz/course/sci/spring2006/Bi8600