The development and advancement of agriculture, veterinary and other life sciences are linked to well-designed experiments, be it in test tubes or in the field, and to the proper use of statistical analysis. The analysis of experiments is crucial for decision making and prediction. Consequently, the choice of appropriate statistical tools is of paramount importance. There are numerous programmes that can be used to analyse experiments. However, there is currently one dominant programme that has caught the interest of theoretical statisticians as well as scientists depending of applied statistics, that is the open source programme and environment R (http://www.r-project.org).
In this series of three courses in applied statistics, we will teach, when and how to use linear and nonlinear models, mixed models, methods for survival analysis, and other advanced techniques that are available in R.
The objective of this series of courses is to build up an environment and network of PhD students and future researchers in the Nordic countries with experience and knowledge of the capability of using one of the most advanced, yet fastest growing statistical software programmes and environments in the world.
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