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 starts with a reminder of the concepts of descriptive statistics taught in secondary school, together with some additional extensions (unit area histogram, computation of quantiles...). Then, some mathematical properties of the parameters and techniques will be developed. Finally, the course ends with 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 (taking into account, for example, the dissymetry of the data) 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 learning activities are diverse
1) Attendance to ex-cathedra lectures for the theory and self-learning of the proofs by means of videos;
2) Self-learnig of the basics of the statistical software via ressources put on line
3) Exercises
4) Multiple questions on line in order to check the comprehension of the basics and properties.
Mode of delivery (face to face, distance learning, hybrid learning)
Blended learning
Additional information:
As far as theory is concerned, one part will be delivered in a face-to-face way and another part in a distance way (by means of videos put on MyUliege). 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.
The tutorials (personnal resolution, with the punctual help of the professor) require the use of a statistical software on a computer. It is possible to bring one's own laptop or to work in groups with someone who has one. Students who do not have a laptop and do not wish to work in groups will have the possibility to take part to the tutorial in a distance way in order to be able to use a non-portable computer
The self-learning of the statistical software will be performed at home but the students will have the opportunity to get help at the tutorials.
Each week, the students will be invited to answer some Multiple choice questions on line.
Recommended or required readings
Notes written in French (on the theory) and the statements of the exercises are available on line (LOL@).
Assessment methods and criteria
Exam(s) in session
Any session
- In-person
written exam ( multiple-choice questionnaire, open-ended questions )
Additional information:
The final mark is a weighted mean of the marks attributed to the following assesments
- written exam on theory and exercises
- Practical exam of the statistical software organized during the session IN THE COMPUTER ROOMS OF HEC
- cumulative results of the 10 on-line tests (any undone test leads to the result 0/5 for that particular test)
Additional information will be given at the beginning of the course concerning the weighting and will be repeated in a final document detailing the constraints to follow during the exams.
However, 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
The organisaiton will be explained at the first lecture and detailled on LOLa.
Contacts
G.HAESBROECK, Institute of mathematics, Building B37, room 0/60, tel: 04/366-95-94,
email: G.Haesbroeck@ulg.ac.be
S. KLENKENBERG,, Institute of mathematics, Building B37, email: s.klenkenberg@uliege.be