Courses open for registration

The design and analysis of experiments, using plants, animals, or humans, are an important part of the scientific process. Proper design of an experiment, apart from its proper analysis and interpretation, is important to convince a researcher that your results are valid and that your conclusions are meaningful.

The main aims of this course are to introduce participants to Big Data and the similarities and differences between regular modeling approaches and big data modeling, to help them understand the possibilities and limitations of R in big data research, to introduce them to high performance computing and to reproducible research. This course is aimed at experienced R users and should not be seen as a course to learn R.

In this module we continue with Regression, ANOVA, and ANCOVA, set in the general framework of Linear Models. We look at topics like parameter estimation and interpretation, checking model assumptions, regression diagnostics, analysis of unbalanced designs and multiple comparisons.

In this course, the participant will be provided with both the basic understanding of the principles of multivariate methods and the skills needed to use those methods in his/her own work. The course consists of lectures and computer practicals using RStudio.

In this module we discuss how to analyse data for which the assumption of independence is violated. So: Do you have a nested experimental set-up? Or repeated measurements? Or weight of the same animal over time? Or pseudo-replication? Then, you are likely to need Mixed Models. In this course, you will learn all about it!

In this module we study how to analyse data that are not normally distributed. We look at fractions (logistic regression), counts (Poisson regression, log-linear models), ordinal data (threshold models), and overdispersion. We discuss (quasi-) maximum likelihood estimation and the deviance.

Classical statistics offers a powerful toolbox for data analysis. This toolbox, however, may not always be sufficiently flexible for modern data situations. The Bayesian framework allows for the integration and inclusion of information from many sources as well as a natural quantification of uncertainty in subsequent analysis.

Resilience is the capacity of a system to maintain or recover certain functions while undergoing shocks and stresses. It emerges from the many interactions between people and natural and/or artificial system components, and the capacity of people to adapt. During this course, the participants become acquainted with different resilience concepts and their application from an interdisciplinary perspective. Accordingly, we will address how resilience theory can be used to tackle fundamental and societal issues from a socio-economic and bio-physical perspective and will provide a critical reflection on the relevance, use, and applicability of the concept of resilience. The objective of this course is thus to connect resilience concepts to viable applications by offering an efficacious analytical/computational approach.

Researchers trying to summarize the constantly growing body of published research are increasingly using meta-analysis. The focus of this 2-day course will be on concepts of linear models and mixed linear models in meta-analysis. The statistical software R will be used.

The Soil Biology Group of Wageningen University is organising a laboratory skills course to define which measurements of soil biology are relevant for which soil functions. This course will provide the participants with an overview of a range of methods related to the five soil functions and will provide detailed practical training in a subset of measures.

In collaboration with SI-MFS initiative (Sustainable Intensification of Mixed Farming Systems) of the OneCGIAR, the PE&RC graduate school again organizes this FSRLA field course. The focus of this edition of the FSRLA course is on farming systems in transition, as climate change, population growth, land use change, and changes in markets pose require a transformation of current food systems, globally.

In this fourth edition of the European Forestry course, organised under the flag of the Euro League for Life Sciences (ELLS), we bring together PhD candidates and lecturers from various countries and backgrounds, and working in different scientific approaches related to European forests. Particular focus of this course will be on the potential contribution of forest management in European forests to biodiversity conservation goals, as well as on conflicts that may arise from forest use, differentiated between different site conditions, resource use, and societal context, and participants will be stimulated to develop novel management strategies to protect and enhance biodiversity while maintaining other forest use as well. The course will be held near Białowieża National Park, Poland.

The aim of this course is to provide an introduction to R and R Studio. It introduces the participants to R language syntax, to enable them to write their own R code. They will also learn about R data-types and data-structures, and they will be taught how to explore the data and produce plots. The course will be a combination of lectures and practicals.

In this workshop, participants will learn the principle of tidy data, how to transform and combine datasets using the tools from the tidyverse and how to generate advanced visualization with the ggplot2 package.

The aim of this course is to provide an introduction to R and R Studio. It introduces the participants to R language syntax, to enable them to write their own R code. They will also learn about R data-types and data-structures, and they will be taught how to explore the data and produce plots. The course will be a combination of lectures and practicals.

Geostatistics is concerned with the analysis and modelling of spatial variability. It also addresses how quantified spatial variability can be used in optimal spatial interpolation and spatial stochastic simulation. Fields of application include hydrology, soil science, ecology, geology, agriculture, and forestry.