Advanced Analytical Methods in Plant Ecology using R

Recommended Prerequisites

Basic knowledge in Ecology, Biology and data sampling.

Teaching Methods

Normal.

Learning Outcomes

Students will gain in-depth knowledge on the preparation, analysis, interpretation and presentation of plant ecological data. They will learn to use the open source software R and choose the appropriate packages for their analyses. This course is a recommended for advanced MSc courses such as eco114 and biol240, and MSc students interested in the analysis of ecological data. By the end of the course students are able to independently prepare ecological datasets for statistical analysis, interpret statistical tests of ecological hypothesis, and present statistical results effectively as required for their own master thesis. Most importantly, they will be able to train themselves in handling statistical challenges in R.. Teamwork will improve interpersonal skills.

Work Placement(s)

No

Syllabus

Compulsory contact hours comprinse a one week full-day block course in the semester break after the winter term. Each day during the block course will consist of lecture hours, followed by 4 seminar hours with exercises during which the students will be intensively supervised.

The course is separated into five to six chapters depending on the knowledge of the participants and may

involve:

1. Introduction into R techniques for an efficient and consistent data analysis,

2./3. linear (generalised) regression models using maximum likelihood estimation ,

4. Mixed-effects models

5./6. Multivariate Analysis (Cluster Analysis, unconstrained and constrained ordination techniques).

Head Lecturer(s)

José Paulo Filipe Afonso de Sousa

Assessment Methods

Assessment
Exercise Protocol : 50.0%
Presentation of results: 50.0%

Bibliography

All primary sources are in English language.

General introductions to statistical methods using R:

- Crawley, M. J. 2012. The R book. 2nd edition. John Wiley, West Sussex, UK 

- Crawley, M. J. 2014. Statistics: An introduction using R. 2nd edition. John Wiley, West Sussex, UK

- Zuur, A. et al. 2009. Mixed effects models and extensions in ecology using R. Springer Verlag, New York.