Duration
30h Th, 10h Pr, 20h Mon. WS
Number of credits
| Master in mathematics (120 ECTS) (Even years, not organized in 2021-2022) | 8 crédits | |||
| Master in mathematics (60 ECTS) (Even years, not organized in 2021-2022) | 8 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 concerns linear models : multiple linear regression, ANOVA, and an introduction to some generalized linear models. Depending on the time constraints, models used in more specific situations might be considered (eg: survival analysis, quantile regression).
Learning outcomes of the learning unit
The student should be able to estimate, validate and interpret a mulitple linear model and an analysis of variance. He·She will be able to recognize situations when the usual hypotheses are violated.
Prerequisite knowledge and skills
Courses of Statistics and Probability and linear algebra included in the program of Bachelor in Mathematics. Some basics of R are also recommanded.
Planned learning activities and teaching methods
- Theory will be exposed using some chapters of reference books.
- Exercises will have to be tackled on an individual basis
- Data analyses will be performed by means of two softwares (R and SAS).
Mode of delivery (face to face, distance learning, hybrid learning)
Blended learning
Additional information:
ATTENTION: this course is only organised every two years (see the section "organisational remaraks").
If the sanitary conditions are favorable, the lectures on theory will be organised face-to-face.
The exercises will have to be done at home. The resolutions or the encountered problems will be discussed from time to time during a lecture or a practical.
Some practicals (data analyses with R and SAS) will also be organised face-to-face.
Recommended or required readings
There is no lecture notes. The slides will be put on eCampus and for each chapter, some referece books will be suggested.
Assessment methods and criteria
Any session :
- In-person
written exam ( open-ended questions )
- Remote
written exam ( open-ended questions )
- If evaluation in "hybrid"
preferred in-person
Additional information:
The mak of the course will be based on two parts:
- Written exam on theory and exercises
- A personal data analysis (with a written report and an oral defense)
Work placement(s)
Organizational remarks
The course is only given on even academic years (20-21, 22-23,...) . Therefore, it will not be taught this academic year 2021-2022.
Contacts
G. Haesbroeck: G.Haesbroeck@uliege.be