This course is the first part of the L3 statistics course, the second part being devoted to tests and model choice. It covers the fundamentals of parametric statistics, both from mathematical and methodological points of view. With some forays into computational statistics. The main theme is that modelling is an inherent part of the statistical practice, rather than an antecedent to the statistical step. Data may be a given, while models almost never are. This means one should keep a critical eye about models and develop critical tools to assess their adequation. Including, first and foremost, an assessment by simulation (Monte Carlo) methods.
As you may have noticed, the course is entirely in English, except for the partial and final exams. This means the practicals (TD) are in English as well and students are expected to communicate in English. There is indeed at least one course taught in English in each semester of the L3 and M1 years: Statistics (1) is the chosen course for the first semester of L3.
This year, some practicals (TP) will be included, covering R language programming and applications to the bootstrap methodology.
Contents
 Statistics, the what and why
 Probabilistic models for statistics
 GlivenkoCantelli theorem, Monte Carlo principles, and the bootstrap
 Likelihood function, geometry, and information
 Likelihood inference
 Bayesian inference
References
 Wasserman, L. (2010) All of Statistics: A concise course in statistical inference. SpringerVerlag [Springer link, with discount code tCmCBtT43NBdmWr] [amazon link]
 Boos, D. and Stefanski, L.A. (2014) Essential statistical inference. SpringerVerlag
 Cadre, B. et Vial. C. (2012) Statistique mathématique  cours et exercices corrigés. Ellipses [en français]
Documents
 Introduction to R, JeanMichel Marin, Robin Ryder and Julien Stoehr
 R scripts for practice, Clara Grazian (.rar format)
 Notes de cours de statistique (Polytechnique), Marc Hoffmann [en français]
 Notes de cours de statistique (MIDO), Marc Hoffmann [en français]
 Statistique mathématique (U Pierre et Marie Curie), Arnaud Leguyader [en français]
 Feuilles de TD 2013, Marc Hoffmann
 slides of the course
 (Chapter 0, Chapter 1, Chapter 2, Chapter 3, Chapter 4)
 TD1, TD2, TD3, complete TD
 TP1(script_example.R, solution), TP2, TP3 (data_uniform.csv, deputes.csv)
 20142015: midterm exam, final exam, solution
 20152016: midterm exam, final exam
 20162017: midterm exam, final exam
 20172018: midterm exam (solution), final exam

