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Course, academic year 2023/2024
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Basics of multivariate data analysis - MO550C19
Title: Basics of multivariate data analysis
Czech title: Základy mnohorozměrné analýzy dat
Guaranteed by: Institute for Environmental Studies (31-550)
Faculty: Faculty of Science
Actual: from 2022
Semester: winter
E-Credits: 3
Examination process: winter s.:
Hours per week, examination: winter s.:0/4, C [DS]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: English, Czech
Note: course is intended for doctoral students only
enabled for web enrollment
Guarantor: RNDr. Mgr. Ondřej Mudrák, Ph.D.
Teacher(s): RNDr. Mgr. Ondřej Mudrák, Ph.D.
Annotation -
Last update: RNDr. Jolana Tátosová, Ph.D. (20.05.2022)
Multivariate analysis of data has a wide range of applications in the biological sciences. A basic knowledge of it will enable students to evaluate changes in species composition of communities, changes of a wide range of
chemicals or other parameters in observations and experiments. The course will emphasize the practical application of these methods on the student's own data or on data provided by the teacher.
Literature -
Last update: RNDr. Mgr. Ondřej Mudrák, Ph.D. (16.05.2023)

Šmilauer, P., & Lepš, J., (2014). Multivariate Analysis of Ecological Data Using Canoco 5. Cambridge University Press, Cambridge, UK.

ter Braak, C.J.F., & Smilauer, P. (2012). Canoco reference manual and user's guide: software for ordination, version 5.0, Microcomputer Power, Ithaca, USA.

Requirements to the exam -
Last update: RNDr. Jolana Tátosová, Ph.D. (20.05.2022)

Credit will be given for the final presentation of the statistical results and conclusions drawn from them.

Syllabus -
Last update: RNDr. Mgr. Ondřej Mudrák, Ph.D. (16.05.2023)

The course will run in two two-day blocks. In the first block, commonly used methods of multivariate data analysis will be introduced and their practical use in Canoco 5 software will be demonstrated.



In the second block, students will present their data that they need to analyze. If they do not have them yet, data will be assigned to student by the teacher. Under the guidance of the teacher, they will then prepare the data in the correct format and analyze it using the appropriate method.

 
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