Advanced inferential statistics - 4MMSIA6

Informations générales

  • 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.

Prerequisites

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

Test

Evaluation : Examen Ecrit (3h)

Resit : Examen Ecrit (2h)

Session 1: written exam (3 hours, handwritten documents allowed) (E).

Session 2: written exam (2 hours, handwritten documents allowed) (E).

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 2025-2026

Additional Information

Course ID : 4MMSIA6
Course language(s): FR

The course is attached to the following structures:

  • Team Probability-Statistics

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.