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The aim of statistics is to provide useful information from random data. This course presents the basic principles of statistical data analysis (description, estimation, tests), and the most usual statistical methods. The focus of the course is application more than theory. The concepts introduced are illustrated with R.
1. Descriptive statistics. Statistical plots. Statistical indicators.
2. Point estimation. Definition and quality of an estimator. Method of moments. Maximum likelihood.
3. Confidence intervals.
4. Testing statistical hypotheses. The decision problem. One-sample parametric tests. Tests on the parameters of a normal distribution, on a proportion. Two-sample tests. Chi-squared test.
5. Linear regression Simple linear regression model. Least squares estimators.
Probability Theory and Applications (first year).
Written exam (3 hours, documents allowed) and project with R.
Note de 1ère session : N1 = 1/5 TP + 4/5 E1
Note de 2ème session : N2 = 1/5 TP + 4/5 E2
Polycopié de cours.
P. DAGNELIE : Statistique théorique et appliquée, 2 tomes, De Boeck Université, 2007.
P. DALGAARD : Introductory Statistics with R, Springer, 2002.
D.C. MONTGOMERY, G.C. RUNGER : Applied Statistics and Probability for Engineers, Wiley, 2003.
G. SAPORTA : Probabilités, analyse de données et statistique, Technip, 2006.
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