6 ECTS credits
166 h study time
Offer 1 with catalog number 4007700FNR for all students in the 1st semester at a (F) Master - specialised level.
This is an applied statistics course specifically designed for biologists and environmental scientists with a focus on biological problems and statistical procedures used in the biological sciences. It contains a brief recapitulation of the fundamental elements of statistical inference, basic procedures such as ANOVA, correlation, regression and contingency tables. These foundations are complemented with an overview of more advanced methods including logistic regression, repeated measures ANOVA, mixed models, general- and generalized linear models as well as a range of non parametric methods. Finally, the course also includes an overview of multivariate analysis techniques including PCA, CCA, RDA and NMDS. Theory will be illustrated with specific biological examples from different research areas and complemented with hands-on practical experience with different statistical approaches in the flexible environment provided by the statistical packages available in the R platform. No prior knowledge of the R language is required to take this course. The emphasis is on performing statistical analyses in R not on programming.
By the end of this course students are expected to:
- have a working knowledge of the different types of basic and more advanced statistical approaches available to analyse biological data.
- be able to choose appropriate statistical methods to analyze biological data
- Be able to correctly perform and interpret results of statistical analyses
- Be able to perform statistical analyses in R
- to have basic knowledge about experimental design, the experimental method and research ethics.
Ultimately, the skills acquired during this course should enable students to independently analyse and interpret biological data in their future professional career as well as in their Master or PhD projects.
The student knows the principles of different types of basic and more advanced statistical approaches available to analyse biological data and is able to apply them. These include regression, correlation, contingency tables, ANOVA, logistic regression, General and Generalized linear models and basic multivariate techniques such as PCA, RDA and NMDS.
The student can choose appropriate statistical methods to analyze biological data
The student can correctly interpret results of statistical analyses
The study can correctly perform statistical analyses in R
The student understands the importance of - and knows the elements of - a correct experimental design, the experimental method and research ethics and is able to apply this knowledge to biological data.
The final grade is composed based on the following categories:
Oral Exam determines 70% of the final mark.
PRAC Paper determines 30% of the final mark.
Within the Oral Exam category, the following assignments need to be completed:
Within the PRAC Paper category, the following assignments need to be completed:
It is an oral examination with a written preparation. It includes two or three open questions and a set of smaller questions. During the oral examination questions can also be asked about the statistical report that was submitted earlier.
This offer is part of the following study plans:
Master of Biology: Education (only offered in Dutch)
Master of Marine and Lacustrine Science and Management: Standaard traject
Master of Biology: Molecular and Cellular Life sciences
Master of Biology: Human Ecology
Master of Biology: AR Erasmus Mundus Joint Master Degree in Tropical Biodiversity and Ecosystems, start at Brussels
Master of Biology: AR Human Ecology 60 ECTS
Master of Teaching in Science and Technology: biologie (120 ECTS, Etterbeek) (only offered in Dutch)