Courses open for registration

This is a refresher course. The level is that of a second course in Statistics. We will refresh basic knowledge of Probability, Statistical Inference (Estimation and Testing), t-tests, simple cases of Regression and ANOVA, Experimental Design, Nonparametric Tests, and Chi-square Tests. Some time is reserved to discuss statistical problems of the participants.

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 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!

Rewilding soils – building novel concepts for restoring soils and their ecology. This is the theme for the 8th edition of the international PhD course on Soil Ecology.

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.

Microbial communities are everywhere and their properties have critical impact on our lives and our planet. But where do these community properties come from? Ultimately properties such as diversity, stability, resilience, function and dynamic evolution arise from the interactions of the constituent microbes with each other and their environment. But how do we connect understanding of the physiology of individual microbes in the lab to the seemingly overwhelming complexity of microbial communities in soil, marine or human environments? What role do model systems play? Are there general principles? How do we connect the different levels of organisation?

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.

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 course will be a combination of lectures and practicals.

In this two week intensive on-site field course we will take a highly multidisciplinary mix of participants and instructors on a tour of the agroecological opportunities and challenges in sub-Saharan Africa. We will visit farming communities across the wide environmental and economic gradients found along the Rift Valley in Kenya, to see how the local biophysical and socio-economic context matters. We will engage in a transdisciplinary learning experience with local stakeholders to come to a common understanding of how agroecological principles can be applied, allowing participants to build understanding and find solutions across disciplinary boundaries in their own work

Insects provide excellent opportunities as a component of livestock feed for a circular and sustainable approach to feed production. The use of insects as feed component relates to various of the Sustainable Development Goals of the United Nations. Residual streams that remain after harvesting the insects may be used to support sustainable crop production.

Our society depends on plants, not only as the primary source of food and dominating role in ecosystems, but also as provider of commodities such as pharmaceuticals and building materials. In many ways plants are essential for human well-being. This course has an attractive program with many expert speakers in the field of environmental signaling in plants.

Young academics have to make a decisive career choice: either pursue a career in science or look at alternative options of which there are many. When thinking about what to choose many questions arise. In the early phase after a PhD it is essential to assess one’s future career and reflect on one's professional ambition and make an in-depth analysis of both professional and personal strengths and weaknesses. It is therefore that Wageningen Graduate Schools (WGS) offers this programme to postdocs and other young academics who have a PhD.

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.

The purpose of this course is to familiarize participants with statistical methods to analyse uncertainty propagation in spatial modelling, such that they can apply these methods to their own models and data. Both attribute and positional errors are considered. Attention is also given to the effects of spatial auto- and cross-correlations on the results of an uncertainty propagation analysis. Computer practicals make use of the R language for statistical computing.

Aquatic ecosystems play a crucial role in human health and well-being. Aquatic systems also provide diverse habitats, support high levels of biodiversity and vital ecosystems services. With over half of the human population currently living in cities, the health of urban waters is becoming ever more vital. Urban aquatic ecosystems, however, are under severe anthropogenic pressure. Unprecedented rates of global change add a sense of urgency to study the impacts of anthropogenic pressures, and to develop ways to restore and improve the robustness of urban aquatic ecosystems against these pressures.