Duration
25h Th, 15h Pr, 10h Mon. WS
Number of credits
| Bachelor in mathematics | 5 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
In this course, the classical methods of inferential statistics will be first developped: point and interval estimation, hypothesis testing. Then, depending on the available time, an introduction to some techniques used in multivariate statistics will be presented (i.e. Principal Component Analysis and clustering).
Learning outcomes of the learning unit
After this course, the students should be able to use appropriate estimation techniques and take decisions based on the result of statistical testing. Moreover, if time allows, they should have acquired the basic approach of high dimensional data analysis.
Prerequisite knowledge and skills
Descriptive statistics and probability.
Planned learning activities and teaching methods
The course consists of ex-cathedra lectures on the theory. Exercises and data analyses on statistical softwares will be suggested and discussed during the practical sessions. Personal work (for ex: first manipulaitons of the softwares) completes the learning.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Recommended or required readings
(Partial) Course notes, slides and exercises sheets will be made available along the year on eCampus.
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions )
Additional information:
The final mark is a weighted mean of the marks attributed to the two following assesments:
- written exam on theory and exercises (without access to personnal notes nor usage of software)
- written exam in the computer room for a data analysis
Work placement(s)
Organisational remarks and main changes to the course
The schedule of the course is given in Celcat.
Contacts
G. Haesbroeck (G.Haesbroeck@uliege.be)