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;
2) Self-learnig of the basics of the statistical software via ressources put on line
3) Data analysis and discussion in small groups
4) Exercises
5) 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)
The courses and the tutorials are given face-to-face (if possible; depending on the sanitary constraints) 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. 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.
Organisational adjustments related to the current health context
In case of a orange/red code decided by the autorities, the following adaptations will be considered:
- Exposition of theory via videos and organisation of some discussion sessions in a virtual class.
- Practicals maintained according to the same schedule but organised via a virtuel class.
- Distance examn with parts on MCQ for the theory and basic exercises and another part for which written resolutions will need to be up-loaded. Checks for the individual characteristic of the exam will be performed and students might be invited to an oral and virtual discussion in case of doubt.
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
Below you will find information on the evaluation methods planned for in-person and remote exams as well as those planned for hybrid sessions. Depending on how the health crisis evolves, the chosen method will be communicated to you no later than one month before the start of the exam session.
Any session :
- In-person
written exam ( multiple-choice questionnaire, open-ended questions )
- Remote
written exam ( multiple-choice questionnaire, open-ended questions )
- If evaluation in "hybrid"
preferred in-person
Additional information:
The final mark is a weighted mean of the marks attributed to the following assesments
- Personal projet on data analysis with the statistical software SAS (during the semester); with a possible (distance) oral evaluation on the day of the exam
- written exam on theory and exercises
- 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 practical organisation of the course during this academic year 20120-2021 will depend on the sanitary conditions.
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