Non parametric statistics

Teacher(s)

Pircalabelu Eugen;

Language

French

Prerequisites

Concepts and tools equivalent to those taught in teaching unit LSTAT2014 : Eléments de probabilités et de statistique mathématique

Main themes

The themes of touched upon in the classroom are :
1.    Parametric vs nonparametric statistics
2.    Nonparametric estimation of a cumulative distribution function
3.    Location problems: the one-sample setting
4.    Location problems: the two-sample setting
5.    Location problems: the K-sample setting
6.    Dispersion problems: the two-sample setting
7.    Goodness of fit testing
8.    Association analysis

Learning outcomes

At the end of this learning unit, the student is able to :
1	The students will obtain knowledge about the basic concepts of nonparametric statistical inference. They will learn about elementary nonparametric testing procedures. They will be able to use these nonparametric procedures for analyzing real data, and this by using, for example, statistical software packages.

Bibliography

• Gibbons, J.D. (1971). Nonparametric Statistical Inference. McGraw-Hill, New York.
• Hollander, M. et Wolfe, D.A. (1999). Nonparametric Statistical Methods. Second Edition. Wiley, New York.
• Lehmann, E.L. (1998). Nonparametrics: Statistical Methods Based on Ranks. Revised First Edition. Prentice Hall, New Jersey.
• Maritz. J.S. (1995). Distribution-free Statistical Methods. Second Edition. Chapman and Hall, New York.
• Mouchart, M. et Simar, L. (1978). Méthodes nonparamétriques. Recyclage en statistique, volume 2. Université catholique de Louvain, Louvain-la-Neuve, Belgique.
• Randles, R. et Wolfe, D. (1979). Introduction to the Theory of Nonparametric Statistics. Wiley, New York.

Teaching materials

• Transparents du cours et syllabus disponible sur Moodle

Faculty or entity

LSBA