Discrete data analysis.

Teacher(s)

Bogaert Patrick ; El Ghouch Anouar ;

Language

Français

Main themes

- Multinomial Distribution : marginal and conditional distributions and asymptotic properties - Two ways Contingency Tables : Independance and Homogeneity, measures of association and particular tests (Fisher, Mac Nemar, etc.). - Multiple ways Contingency Tables : Mutual, Partial and Conditional Independencies. - Log-linear Models. - Conditional Models - Generalized Linear Models - Logit and Probit Models - Multinomial Discriminant Analysis - Selection of explanatory variables

Aims

The student will be able to use the basic techniques of Discrete Data Analysis and to apply these to real data using statistical softwares

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.

Content

Content - Multinomial Distribution : marginal and conditional distributions and asymptotic properties - Two ways Contingency Tables : Independance and Homogeneity, measures of association and particular tests (Fisher, Mac Nemar, etc.). - Multiple ways Contingency Tables : Mutual, Partial and Conditional Independencies. - Log-linear Models. - Conditional Models - Generalized Linear Models - Logit and Probit Models - Multinomial Discriminant Analysis - Selection of explanatory variables Methods The course is concentrated on the first ten weeks. The following 4 weeks are devoted to the realization by each student of an empirical study of suitable data.

Other information

Prerequisites : Elementary courses in Probability and Statistics Evaluation Each student is provided a data set to be analyzed by the taught techniques. This analysis is the object of a report orally presented by the student to the Professors. During this presentation, the Professors may question the student on the matter of the course. Support The third reference is the basic reference. Other materials will be provided to students. Assistant Isabelle De Macq References Bishop Y.M.M., Fienberg S.E. and P.W. Holland (1975) : Discrete Multivariate Analysis, Theory and Practice, M.I.T. Press, Cambridge, Mass. Dobson Annette (1990) : An Introduction to Generalized Linear Models, Chapman and Hall, London. Gérard G. and J.M. Rolin (1979) : Analyse des données discrètes, Recyclage en statistique, vol. 3, Université catholique de Louvain, Louvain-la-Neuve.

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> LSBA