Duration
20h Th, 20h Mon. WS
Number of credits
| Master in mathematics (120 ECTS) | 4 crédits | |||
| Master in mathematics (60 ECTS) | 4 crédits |
Lecturer
N...
Substitute(s)
Language(s) of instruction
French language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This course aims at providing students with some tools for working on applied statistical problems, acting as a consultant for a non-statistician client.
The course includes
- the role and the posture of the consultant ;
- good scientific practices and critical thinking ;
- the appropriate use of statistics ;
- the efficient communication of statistical methods and results ;
- softwares ;
- project management.
Learning outcomes of the learning unit
The course discusses the role of the statistician consultant involved in data analysis projects and introduces some usefull tools in this context.
Prerequisite knowledge and skills
The courses of statistics from the Bachelor in Mathematics are prerequisites.
Good knowledge and easy use of R and / or SAS statistical software is necessary.
The course mainly concerns students from the Master in Mathematics.
Planned learning activities and teaching methods
The course consists in a series of lectures where an active participation of the students is expected. Case studies will be proposed and group work will be requested. If possible, meetings with some professionals will be organized. A project will be proposed to the students.
Mode of delivery (face-to-face ; distance-learning)
The course consists in a series of lectures where an active participation of the students is expected. Case studies will be proposed and group work will be requested. If possible, meetings with some professionals will be organized. A project will be proposed to the students.
Recommended or required readings
Required material will be provided via eCampus.
Assessment methods and criteria
The final score is a weighted average based on the results obtained in the following tests :
- personal or group work during the term
- report writing
- oral presentation of the project
Work placement(s)
Organizational remarks
The course is organised only on odd years (2019-2020 is the next session).
Contacts
Marie Ernst
CHU de Liège, SIMÉ, Secteur d'Appui à la Recherche Clinique et Biostatistique.
Université de Liège, Département de Mathématique.
Mail : m.ernst@chuliege.be
Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session
Teaching methods implemented : distance-learning
Since March 13, 2020, videos explaining the content of the slides are available online. Some wooclap exercises are proposed in complement.
Video conferences are organized with students at the regular class schedule (see online schedule).
The practical work is maintained at home.
The practical details are explained on eCampus.
Assessment subjects
No modification.
Assessment methods
The final score is a weighted average based on the results obtained for the following tests:
- personal work during the term (20%)
- report writing (50%)
- online oral presentation of the project (30%)
Contacts
Marie Ernst
CHU de Liège, SIMÉ, Secteur d'Appui à la Recherche Clinique et Biostatistique.
Université de Liège, Département de Mathématique.
Mail : m.ernst@chuliege.be
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
No modification
Assessment methods
Same evaluation than in June : a report writing and online oral presentation of the project (via Lifesize).
Contacts
Nathalie Maes (CHU de Liège) : nmaes@chuliege.be