Duration
35h Th, 15h Pr
Number of credits
| Bachelor in business engineering | 4 crédits |
Lecturer
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
The course is divided into two parts: descriptive statistics and (an introduction to) probability theory. The learning of a statisitcal software is also a part of the course.
Learning outcomes of the learning unit
After this course, the student should be able to represent data by means of appropriate tables and graphs, compute appropriate parameters in order to analyse data and to use correctly probability calculus.
More globally, the student will need to demonstrate a critical mind and scientific precision in the analysis of statistical information and should be able to use the appropriate analytical tools for the description of data.
Prerequisite knowledge and skills
No prerequisite
Planned learning activities and teaching methods
The course is divided into three parts:
- Theory
- Tutorials (exercises)
- Learning of a statistical software
The type of teaching for the theory part is ex-cathedra. The professor uses beamer projections or writes on the black boards. When slides are used, these will be available in advance on Lol@.
The tutorials combine ex-cathedra presentation and individual work for the students. Moreover, before each tutorial, the students will be invited to test their knowledge by means of multiple choice questions on line.
The statistical software will be taught mainly by self-learning using videos put on line.
Mode of delivery (face-to-face ; distance-learning)
The courses and the tutorials are given face-to-face over the second semester according to a timetable distributed to the students in the beginning of the academic year. When the lecture room will allow it, the theory lectures will be recorded by podcast. The students will then have the opportunity to visualize the recording when they want. Additional information on the self-learning sessions on the statistical software will be given to the students at the beginning of the course.
Recommended or required readings
Notes written in French (on the theory and on the exercises) are available in university shop.
Assessment methods and criteria
The final mark is a weighted mean of the marks attributed to the two following assesments taking place in may-June:
- written exam on exercises and theory
- practical exam on computer
A document detailing the constraints to follow during the exams will be available on line as soon as the course ends. More details on the computation of the average will be given there but it is already indicated here that a very bad mark (below 5/20) in at least one theme of the course (descriptive statistics - probability - statistical software) will imply a global grade below 10/20.
Work placement(s)
Organizational remarks
None
Contacts
G.HAESBROECK, Institute of mathematics, Building B37, room 0/60, tel: 04/366-95-94,
email: G.Haesbroeck@ulg.ac.be
M. ERNST, Institute of mathematics, Building B37, email: m.ernst@ulg.ac.be
S. AERTS, HEC-ULg, Building N1, email: stephanie.aerts@ulg.ac.be