300224 VU Multivariate statistical methods in ecology (2021S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Th 11.02.2021 08:00 to Th 25.02.2021 18:00
- Deregistration possible until We 31.03.2021 18:00
Details
max. 25 participants
Language: English
Lecturers
Classes
The course is scheduled as one block, from March 8-12, daily from 0900-1700. The entire class will be in distance-learning format and held online.
Information
Aims, contents and method of the course
Assessment and permitted materials
Presence throughout the course is compulsory.A written exam of 2 h length, comprising a theoretical and a practical part, will be held at the end of the class. A second and a third opportunity will be offered in accordance with the participants
Minimum requirements and assessment criteria
A general understanding of R is mandatory for the course.
Successful participants will gain a working understanding of the mathematical and computational mechanics behind the most commonly used statistical methods in ecology. They will understand how to interpret graphical and tabular output from univariate, bivariate and multivariate analyses of ecological datasets as presented in scientific papers and reports. The lecture also explains backgrounds of statistical thinking, hypothesis testing, study planning and experimental design.
The written exam and test exercises will focus on these aspects, and a total of 20 points may be awarded, where the following total points correspond to grades 5-1: 0-10 points = 5, 11-13 = 4, 13-15 = 3, 15-17 = 2, >18 = 1.
Successful participants will gain a working understanding of the mathematical and computational mechanics behind the most commonly used statistical methods in ecology. They will understand how to interpret graphical and tabular output from univariate, bivariate and multivariate analyses of ecological datasets as presented in scientific papers and reports. The lecture also explains backgrounds of statistical thinking, hypothesis testing, study planning and experimental design.
The written exam and test exercises will focus on these aspects, and a total of 20 points may be awarded, where the following total points correspond to grades 5-1: 0-10 points = 5, 11-13 = 4, 13-15 = 3, 15-17 = 2, >18 = 1.
Examination topics
Successful participants will be capable of interpreting statistical testing theory, applying and justifying conventions as well as analyzing data sets. They can propose testing schemes for datasets/problems and develop and implement a testing approach based on an example data set.
Reading list
Literature will be provided in form of a course hand-out; additional literature will be presented during the class
Association in the course directory
MEC-5, UF MA BU 01, UF MA BU 04
Last modified: Th 04.03.2021 15:29
We aim at providing an overview (including theoretical background) on statistical testing, in combination with a practical part during which students are to acquire the capacity to independently implement statistical testing strategies.
Lectures on theory and derivation of statistical methods are combined with hands-on R scripting to achieve this goal.