For more information about a MSc thesis at WEC, please see our Brightspace page.
As a student you should enrol yourself to this discoverable 'course' in Brightspace (i.e. the Brightspace course: Thesis and Internships Wildlife Ecology and Conservation). See instructions here.
The MSc-thesis offers the challenge to demonstrate your ability to set up and to carry out a scientific research project in a self-responsible and independent manner. This challenge includes to:
- provide an adequate delineation and definition of your research topic,
- build a sound theoretical framework for orientation of the research,
- generate proper research questions and/or testable hypotheses,
- develop methodology fit for hypothesis testing,
- collect data in a systematic and verifiable manner,
- analyse the data critically and correctly,
- present the results in a comprehensible manner,
- draw sound conclusions based on a comprehensive discussion of the results,
- show the contribution of your results to the development of the research topic.
A thesis project using R
The majority of the students working on their thesis at WEC will come into contact with the programming language R. With R you can do more advanced data processing, statistics and visualization than with, for example, SPSS and Excel. Also, it is free and open-source. Here, we provide some information on how to gain experience with R.
We encourage students who want to do their thesis at WEC to follow at least one of the below-mentioned WU courses. If this is not possible, then take the time the work through the R tutorial and/or the R online course before you start with your WEC thesis.
- REG-33806 Data Science for Ecology: using R for data science, machine learning and artificial intelligence.
- FEM-31806 Models for Ecological Systems: using R to create and evaluate simulation models.
- CSA-34306 Ecological Modelling and Data Analysis in R: using R to fit statistical models to your data and for visualization.
- MAT-50303 R for Statistics: using R for hypothesis and statistical significance testing.
- Learning the basics of R and RStudio step-by-step with this tutorial, including an interactive tutorial using R itself with the swirl-package: https://emethods.nl/rintro/
- Learning to use R for statistical test: https://emethods.nl/r/
- A free online course in which you learn the basics and more advanced skills of working with R for data analysis: https://www.coursera.org/learn/r-programming