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  Prospectuses 2012-2013
Radboud universityProspectusesFaculty of Science > Bachelor Biologie

Ecological Theory and Data Analysis 

Course ID
NWI-BB083B
Credits
6
Scheduled
third quarter
Teaching methods
  • 4 hrs guided individual project work
  • 46 hrs computer course
  • 4 hrs excursion
  • 18 hrs lecture
  • 4 hrs student presentation
  • 82 hrs individual study period
Pre-requisites


Objectives

The purpose of this course is to have you become familiar with 1) the use of theoretical models in ecology, 2) statistical analyses that are particularly used in ecological research, and 3) modelling in R.

The value of computer models for developing and analyzing theories in ecology will be illustrated with lectures on case studies, and with computer exercises in which you will learn to develop, code and analyze simple models.

Data, resulting from ecological experiments and observations in the field, often require a more advanced statistical toolbox. In this course you will learn how to decide what type of statistical analysis fits particular data and research questions. You will learn to apply analysis tools that are commonly applied in ecological research, and how to interpret the resulting statistics. The goal is to be well prepared for analyzing data that you might generate during a future MSc project.

The software R is increasingly used in many fields of science, including ecology. Learning to program in R is thus a useful skill for many types of research. Other benefits of R include that it is free, requires understanding of the process at hand (no pull-down menus), is useful for combining statistical analyses and modelling, can produce high-quality graphs, and is constantly further developed (through packages contributed by experts in their respective fields).

Contents

Theoretical and statistical models are often used in ecological research. Simple models are very useful tools for gaining insight in the mechanisms and consequences of theories in ecology. In this course we will first explore e.g. invasion, metapopulation, coexistence and species interaction models. In the second part of the course we will focus on the analysis of ecological data, which are often complex. Topics covered include e.g. model choice, (multivariate) regression analyses, principle component analyses, capture-mark-recapture analyses and model selection. All modelling during the course will be done using the freely-available software R.

Subjects

In this course we will for instance explore invasion, metapopulation, coexistence and species interaction models. Topics covered in the second part of the course include e.g. model choice, (multivariate) regression analyses, principle component analyses, capture-mark-recapture analyses and model selection.

Literature

Will be provided at the beginning of the course (through Blackboard)

Extra information

Contact: drs. P. Charpentier, HG 01.021, 3652902,

The course is on Thursdays and Fridays