Ensimag Rubrique Formation 2022

Statistical principles and methods - 3MMPMS

  • Number of hours

    • Lectures 16.5
    • Projects -
    • Tutorials 13.5
    • Internship -
    • Laboratory works 3.0
    • Written tests -

    ECTS

    ECTS 3.0

Goal(s)

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.

Responsible(s)

Olivier GAUDOIN

Content(s)

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.

Prerequisites

Probability Theory and Applications (first semester).

Test

Practical work with R.
Written exam (3 hours, documents allowed), with a part on R.

    • MCC en présentiel **
      N1=1/4*TP en temps libre + 3/4*Examen écrit
      N2=1/4*TP en temps libre + 3/4*Examen écrit
    • MCC en distanciel**
      N1=1/2*TP en temps libre + 1/2*Examen à distance
      N2=1/2*TP en temps libre + 1/2*Examen à distance

Calendar

The course exists in the following branches:

  • Curriculum - Core curriculum - Semester 6
see the course schedule for 2023-2024

Additional Information

Course ID : 3MMPMS
Course language(s): FR

The course is attached to the following structures:

You can find this course among all other courses.

Bibliography

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.