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R and Big Data
Thursday 26 - Friday 27 September 2019
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.
Bayesian Statistics
Wednesday 23 - Thursday 24 October 2019
Nowadays, with the advance of computing and Markov Chain Monte Carlo (MCMC) algorithms, Bayesian statistics is becoming a powerful alternative for traditional Frequentistic statistics. Participants will be surprised how easy they can tackle problems that are quite complicated to handle with traditional Frequentistic statistics.
Intro to R for statistics (November 2019)
Wednesday 6 - Thursday 7 November 2019
The aim of this course is to provide an introduction to R, a language and environment for statistical computing and graphics. Focus of the course will be on getting familiar with the R environment, to use R for manipulation and exploration of data, and to perform simple statistical analyses. Hands-on exercises will form a large part of the workshop.
Basic Statistics (November 2019)
Wednesday 20, Thursday 21, Tuesday 26 - Thursday 28 November 2019
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.
Geostatistics
Monday 2 - Friday 6 December 2019
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.
Statistical Uncertainty Analysis of Dynamic Models
Monday 9 - Friday 13 December 2019
The purpose of this course is to make the participants familiar with general statistical concepts describing uncertainty, and methods to compute prediction uncertainty coming from uncertain parameter values. We introduce dynamic input-state-output systems and methods to write your model in this format.
WIAS/PE&RC advanced statistics course Design of Experiments (December 2019)
Tueday 17 December 2019 - Thursday 19 December 2019
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.