Duration
9h Th, 9h Pr
Number of credits
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
Principal component analysis
- aim
- principle
- case studies
Cluster analysis
- aim
- principle
- case studies
Discriminant analysis
- aim
- principle
- case studies
Learning outcomes of the learning unit
To learn how to make a basic mutivariate statistical analysis and how to interpret related software outputs
After completing the course the student is expected to
- identify the cases that should be analysed by principal component analysis, cluster analysis and classification,
- perform these analyses by means of a statistical software,
- correctly interpret the results of the computer output.
Prerequisite knowledge and skills
Basic skills in applied statistics, for example :
- STAT2003 et STAT2004 - Applied Statisticw (1st & 2nd part)
- INFO2037-1- Introduction to computer science
Planned learning activities and teaching methods
Lectures Exercises on computers
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face
Course materials and recommended or required readings
Syllabus
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 remote
Additional information:
Written examination (100%)
Work placement(s)
Organisational remarks and main changes to the course
Lectures : 9 h
Practical Works : 9 h
Participation in all organized learning activities is mandatory
Contacts
Yves Brostaux (Professor)
081 62 24 69
y.brostaux@uliege.be
Association of one or more MOOCs
Items online
eCampus
Course and practical sessions materials