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| ENVT3024-1 | Introduction to the decision-making aid under the Bayesian paradigm
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| Duration : | 24h Th, 24h Pr |
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| Number of credits : |
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| Lecturer : | Jean-Jacques Boreux |
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Language(s) of instruction :
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| French language |
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Organisation and examination :
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| Teaching in the first semester, review in January |
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Course contents :
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| This course is an introduction to Bayesian Hierarchical Modelling where a model appears as a set of stochastic nodes connected by arrows expressing a causal link between the node « parent » and the node « child « . It is the creative part where the student demonstrated imagination to mimic nature which has produced the available sample. This network can be seen as a series of instructions producing data similar to available observations. Inference or technical part consists to move from observed effects (observations) to causes that produced them (the unknown parameters) using Bayes rule. The intensive use of the methods of Monte Carlo Markov Chain (MCMC) liberates student from most of technical difficulties as much as we use WinBUGS a free software linked to R by the package R2WinBUGS. |
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Learning outcomes of the course :
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| Train the student to the production of information relevant from a sample of raw data (measures or field observations) in order to help decision maker. In this perspective, the quantification of uncertainties is essential. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| The student is supposed have basic knowledge in mathematics (secondary level), in statistics (Bachelor level) and he knows the standard laws (Bernoulli, binomial, Poisson, normal) and he is able to manipulate a computer and he can write a simple code. |
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Planned learning activities and teaching methods :
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| The course is a succession of theoretical courses followed by practical work under the leadership of the Professor, and then in the form of exercises to perform alone or group depending on the case. |
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Mode of delivery (face-to-face ; distance-learning) :
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| Face-to-face for theoretical courses and some practical works |
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Recommended or required readings :
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| Pratique du calcul bayésien (Boreux et al., 2010) |
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Assessment methods and criteria :
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| The control of knowledge consists of a problem that the student performs on his laptop during a limited time (typically three hours) and at the end of which he sends a file saved as Professor email address. The exam is open book and the evaluation criteria exclude therefore the reproduction of knowledge to focus on creativity, common sense and critical analysis of the results obtained. |
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Work placement(s) :
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| None. |
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Organizational remarks :
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| None. |
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Contacts :
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| jj.boreux@ulg.ac.be
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