Duration
30h Th, 10h Pr, 20h Mon. WS
Number of credits
| Master in mathematics (120 ECTS) | 8 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This course develops the following themes:
- Ranks and quantiles;
- Non parametric univariate tests;
- Boostrap;
- Non parametric estimation of density functions;
- Non parametric and quantile regression;
- Introduction to robust statistics
Learning outcomes of the learning unit
At the end of the course, students will be able to use, in an appropriate way, nonparametric or robust techniques in inference, regression and density estimation.
Prerequisite knowledge and skills
Inferential statistics (for example: probability and statistics III in the bachelor in mathematics)
Planned learning activities and teaching methods
The course will be divided in ex-cathedra lectures for the theory and practicals for the exercises (ex-cathedra or in the computer room).
Mode of delivery (face-to-face ; distance-learning)
The course is taught only every other year, on "even" years (it will be taugh in 2018-2019).
Recommended or required readings
Some partial lecture notes are available. Moreover, the slides used during the class will be available on eCampus.
Assessment methods and criteria
The evaluation is divided into two parts:
- an exam organised in January with a written part for the exercises and an oral part for the theory.
- homeworks that will be given throughout the first semester and that will be made with the software R.
Work placement(s)
Organizational remarks
Teaching language: French
Contacts
Gentiane Haesbroeck, G. Haesbroeck@ulg.ac.be
Teaching Assistant: Marie Ernst, M.Ernst@ulg.ac.be