<- Archives UCL - Programme d'études ->



Probability and statistics (II) [ LBIR1304 ]


3.0 crédits ECTS  22.5 h + 22.5 h   1q 

Teacher(s) Bogaert Patrick ;
Language French
Place
of the course
Louvain-la-Neuve
Prerequisites

LBIR1203  Probabilité et statistique I

Main themes

Introduction to statistics - Common methods for point estimation - Confidence interval for a mean and a variance - Hypothesis testing and inference - Linear models and regression.

Aims

a.     Contribution of this activity to the learning outcomes referential :

1.1, 2.1

b.     Specific formulation of the learning outcomes for this activity

A the end of this activity, the student is able to :

·       Name, describe and explain the theoretical concepts underlying the statistical inference approach and the theoretical models that are used in this framework;

·       Connect the deductive approach of probability theory to the inductive approach of statistical inference by clearly identifying the probabilistic models that are subject to this inference;

·       Translate mathematically textual statements if an inferential problem in statistics by using a rigorous mathematical and appropriate statistical models and by relying on appropriate theoretical tools and estimation methods;

·       Solve an applied problem by using a sound approach that relies on a correct use of well identified models and relevant tools of the inferential statistical framework;

·       Validate the internal consistency of the mathematical expressions and results based on data at hand and logical constraints that are induced by the statistical framework;

Evaluation methods

Evaluation: Open book written examination (only with the original material). The examination is composed of exercises to be solved. Its duration is about 3 hours.

Teaching methods

Regular courses and supervised practical exercises

Content

The course will complete the basic notions already presented during the course LBIR 1203 - Probability & Statistics. The student will be able to use the most classical estimation and inference methods for one or two means or variances, as well as for the most classical linear models. Few exercises will be devoted to the use of computer software in order to illustrate the various concepts.

Cycle et année
d'étude
> Bachelor in Bioengineering
> Bachelor in Information and Communication
> Bachelor in Philosophy
> Bachelor in Pharmacy
> Bachelor in Computer Science
> Bachelor in Economics and Management
> Bachelor in Motor skills : General
> Bachelor in Human and Social Sciences
> Bachelor in Sociology and Anthropology
> Bachelor in Political Sciences: General
> Bachelor in Mathematics
> Bachelor in Biomedicine
> Bachelor in Engineering
> Bachelor in religious studies
> Preparatory year for Master in Statistics: Biostatistics
Faculty or entity
in charge
> AGRO


<<< Page précédente