ECTS
2 credits
Training structure
Faculty of Science
List of courses
Choose 1 out of 3
Agroforestry
2 credits15hBayesian approach to variability
2 creditsStrategic Analysis of Environmental Management
2 credits
Agroforestry
ECTS
2 credits
Training structure
Faculty of Science
Hours per week
15h
Bayesian approach to variability
ECTS
2 credits
Training structure
Faculty of Science
1. Bayesian inference: Motivation and simple example.
2. The likelihood.
3. A detour to explore priors.
4. Markov chain Monte Carlo methods (MCMC)
5. Bayesian analyses in R with the Jags software.
6. Compare scientific hypotheses with model selection (WAIC).
7. Heterogeneity and multilevel models (also known as mixed models).
Strategic Analysis of Environmental Management
ECTS
2 credits
Training structure
Faculty of Science
Strategic Environmental Management Analysis (SEMA) is a theoretical framework that provides a basis for analyzing a management situation based on a clearly expressed environmental concern. It sheds light on the exercise of environmental responsibility in relation to the exercise of other collective responsibilities, within the context of a pluralistic debate. By identifying the basic structures of environmental management situations, particularly in international contexts, it provides criteria that explain the difficulties faced by public environmental policies in emerging in relation to other areas of public action—particularly development policies – and, on the other hand, identify the scope for promoting change towards greater responsibility for environmental issues. The module is based on two key elements: (1) The presentation of various research-intervention projects using this analytical framework to explain the implementation of the ASGE's working registers, (2) A supervised project combining critical analysis of environmental project documents with the development of an alternative research-intervention study proposal using the ASGE framework, which is presented and discussed collectively at the end of the module.