The course Multivariate Analysis offers a thorough introduction to multivariate statistical methods, tailored for researchers working with complex datasets where multiple variables are measured simultaneously. It is particularly relevant for those analysing data from fields such as ecology, agriculture, environmental sciences, and related disciplines, where observations often include numerous interdependent variables. Participants will learn to address challenges common in such datasets, including multicollinearity, high dimensionality, and the need for effective visualization. Key topics include principal component analysis, redundancy analysis, correspondence analysis, clustering, and other ordination methods, alongside foundational techniques like multiple linear regression, logistic regression, and loglinear models. These regression-based methods are essential for understanding relationships between variables, modelling outcomes, and handling categorical data. The course balances theoretical insights with practical applications, emphasizing the importance of selecting appropriate techniques to answer specific research questions. Participants will explore how to uncover patterns, reduce dimensionality, and interpret complex relationships within their data. Special focus is given to methods for visualizing multivariate results and communicating findings effectively. Through interactive lectures and hands-on exercises, participants will gain the skills to apply multivariate techniques. By the end of the course, they will be well-prepared to analyse their own data, whether it involves exploring ecological gradients, studying community composition, interpreting multi-response agricultural trials, or modelling complex systems using regression approaches.
Target Group | The course is aimed at PhD candidates, postdocs, and other academics that are working above plant integration level in plant, animal, and/or environmental/ecological sciences |
Group Size | Min. 15 / Max. 24 participants |
Course duration | 5 days |
Language of instruction | English |
Frequency of recurrence | Annually |
Number of credits | 1.5 ECTS |
Lecturers | Ir. Saskia Burgers (Wageningen UR) and dr. Jos Hageman (Biometris, Wageningen UR) |
Prior knowledge | Participants are expected to have a good knowledge of basic statistics (like hypothesis testing, t- and F-tests and linear regression) and some experience in a statistical package (GenStat, R, SPSS, or likewise) |
Location | Wageningen University Campus |
Accommodation | Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For non-WUR PE&RC members 50% of the accommodation costs can be reimbursed with a maximum of €30,- per night. For information on B&B's and hotels in Wageningen please visit Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Finally, there are a number of groups on Facebook where students announce subrent possibilities and things like that. Examples include: Wageningen Room Subrent, Wageningen Room Sublets, Room Rent Wageningen, and Wageningen Student Plaza. Note that besides the restaurants in Wageningen, there are also options to have dinner on Wageningen Campus. |
Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl
At this moment, this course is not scheduled yet. However, if you register your interest in this activity below, we will inform you as soon as the course is scheduled and registration of participation is opened.