Ensimag Rubrique Formation 2022

Advanced inferential statistics - 4MMSIA6

  • Number of hours

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

    ECTS

    ECTS 3.0

Goal(s)

This course presents the mathematical theory of statistical inference. It deepens and completes the Statistical Principles and Methods course.

Responsible(s)

Olivier GAUDOIN

Content(s)

1. Concepts of statistical inference. Statistical model. Likelihood. Sufficiency.
2. Optimal parametric estimation. Minimum variance unbiased estimation. Fisher Information.
3. Maximum likelihood estimation. Likelihood ratio tests.
4. Nonparametric estimation. Order and rank statistics.
5. Extreme values statistics.
6. Functional estimation.
7. Goodness-of-fit tests.

Prerequisites

Probability Theory and Applications, Statistical Principles and Methods (first year).

Test

Written exam (3 hours, documents allowed) (E).

    • MCC en présentiel **
      N1=Examen écrit
      N2=Examen écrit
    • MCC en distanciel**
      N1=Examen à distance
      N2=Examen à distance

Calendar

The course exists in the following branches:

  • Curriculum - Financial Engineering - Semester 8
  • Curriculum - Math. Modelling, Image & Simulation - Semester 8
see the course schedule for 2023-2024

Additional Information

Course ID : 4MMSIA6
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.
D. FOURDRINIER : Statistique inférentielle, Dunod, 2002.
J.A. RICE : Mathematical Statistics and Data Analysis, Duxbury Press, 2006.
G. SAPORTA : Probabilités, analyse des données et statistique, Technip, 2011.
J. SHAO : Mathematical Statistics, Springer, 2003.
P. TASSI : Méthodes statistiques, Economica, 2004.