Applied statistics workshops

lstat2390  2024-2025  Louvain-la-Neuve

Applied statistics workshops
3.00 credits
15.0 h
Q1 and Q2
Language
Prerequisites
Professional integration activity
Concepts and tools equivalent to those taught in teaching units
LSTAT2110Analyse des données
LSTAT2120Linear models
LSTAT2100Modèles linéaires généralisés et données discrêtes
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.
Learning outcomes

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.
 
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.
Teaching methods
Online seminar for the first semester and face-to-face or online for the second semester depending on the evolution of the situation.
Evaluation methods
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. The oral exam is then based on a choice of 2 seminars, for wich they review their content, and prepare short talks which render the essential content and situates the talks in a wider context. At least one of the two talks must be made in English. 
Students present the exam in small groups and are evaluated on their talks but also on their participation during the presentations of other students (questions/answers).
This evaluation will be organized face-to-face or remotely (via Teams) according to the evolution of the situation.
Online resources
The slides of the seminars will be made available to students via Moodle (or on request to the professor in case of confidentiality problems).
Teaching materials
  • transparents sur moodle
Faculty or entity


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

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science : Statistic

Master [120] in Statistics: Biostatistics

Master [120] in Statistics: General

Master [120] in Electro-mechanical Engineering

Master [120] in Mathematical Engineering

Master [120] in Data Science Engineering

Master [120] in Data Science: Information Technology

Master [120] in Energy Engineering