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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. Chi-squared test.
5. Linear regression Simple linear regression model. Least squares estimators.
Probability Theory and Applications (first semester).
Practical work with R.
Written exam (3 hours, documents allowed), with a part on R.
N1=1/4*TP + 3/4*E1
N2=1/4*TP + 3/4*E2
The course exists in the following branches:
Course ID : 3MMPMS
Course language(s):
The course is attached to the following structures:
You can find this course among all other courses.
Polycopié de cours.
P. DAGNELIE : Statistique théorique et appliquée, 2 tomes, De Boeck Université, 2015.
P. DALGAARD : Introductory Statistics with R, Springer, 2008.
D.C. MONTGOMERY, G.C. RUNGER : Applied Statistics and Probability for Engineers, Wiley, 2013.
G. SAPORTA : Probabilités, analyse de données et statistique, Technip, 2011.
Date of update January 15, 2017
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