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...) and follows with the introduction of some new concepts useful in management.
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:
The theory lectures are delivered in a face-to-face way and, when the lecture room will allow it, they will be recorded by podcast. The students will then have the opportunity to visualize the recording when they want.
The tutorials will consist of exercises solved by the professoras well as some personal work on the statistical software (during the tutorial or at home).
The self-learning of the statistical software will be performed at home but the students will have the opportunity to get help during one or two Q/A sessions organised during the semester.
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@).
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 change of the weigths used in the average.
Work placement(s)
Organisational remarks and main changes to the course
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@uliege.be