5.00 credits

30.0 h + 7.5 h

Q2

Teacher(s)

El Ghouch Anouar;

Language

French

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

Learning outcomes

| |

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

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.

Evaluation methods

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.

Other information

Prerequisites : Elementary courses in Probability and Statistics

Teaching materials

- transparents sur moodle

Faculty or entity

**LSBA**

#### Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme

Sigle

Credits

Prerequisites

Learning outcomes

Master [120] in Statistics: General

Master [120] in Statistics: Biostatistics

Master [120] in Economics: General

Certificat d'université : Statistique et sciences des données (15/30 crédits)

Master [120] in Mathematical Engineering

Master [120] in Data Science : Statistic