3 credits
15.0 h
Q1 and Q2
Teacher(s)
Legrand Catherine; Ritter Christian;
Language
English
Prerequisites
The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
Each seminar (1 hour) is presented by a different speaker coming from a private or public company or from universities. The themes can be applications of statistical tools to various application domains, tutorials on recent statistical domains or methodological aspects of applied statistics and statistical consulting.
The presentations are more focused on the methodological aspects and main results than on the mathematical details of the discussed problems.
Aims
At the end of this learning unit, the student is able to : | |
1 | Participants in this course will learn about applying statistical thinking in real life problems and about recent statistical advances with immediate practical potential. This seminar publicly announced offers to a public of applied statisticians a place to meet and to present and discuss their work. It gives the opportunity to the students to open their mind to various application domains of statistics. |
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
Each seminar (1 hour) is presented by a different speaker coming from a private or public company or from universities. The themes can be applications of statistical tools to various application domains, tutorials on recent statistical domains or methodological aspects of applied statistics and statistical consulting.
The presentations are more focused on the methodological aspects and main results than on the mathematical details of the discussed problems.
Other information
Prerequistes
Courses of the DEC in statistics
Evaluation
Students who wish to attend this seminar for credit must attend a sufficient
number of presentations and participate actively in the discussions following the
participations. They then select two of the seminars, review their content, and prepare
short talks which render the essential content and situates the talks in a wider context.
Faculty or entity
LSBA
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Data Science Engineering
Master [120] in Statistics: Biostatistics
Master [120] in data Science: Statistic
Master [120] in data Science: Information technology