The objective of this course is to show students how statistics is used in practice to answer a specific question, by introducing a series of important model-based approaches.
The students will learn to select and use appropriate statistical methodologies and acquire solid and practical skills by working-out examples on real-world data sets from various areas including medicine, genomics, ecology, and others.
All analyses will be conducted with the R software. No strong knwoledge neither of R programming is required (only basic scripting).
Course Evaluation: 1 or 2 group projects + 1 PC report + a final exam
Course Language: French with all material in English
Website: https://jchiquet.github.io/MAP566/
Syllabus
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Statistical tests (x2)
- Two-populations comparison
- Power analysis
- Multiple Testing
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Regression models (x2)
- Linear and Non Linear Regression models
- Nonlinear regression models
- Inference Diagnostic, Model comparison
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Mixed effects models (x2)
- Linear mixed effects models
- Nonlinear mixed effects models
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Mixture models and model-based clustering (x3)
- Gaussian mixture models for data clustering
- Stochastic Block Models for graph clustering
- (Variational) EM algorithm
Langue du cours : Français
Credits ECTS : 4
- Profesor: Chiquet Julien
- Profesor: Naulet Zacharie