Study programme 2018-2019Français
Statistique multidimensionnelle
Programme component of Master's Degree in Physics à la Faculty of Science
CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCPHYS-028-MOptional UEVOUE MichelS878 - Physique des matériaux et Optique
  • VOUE Michel

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français151500033.002nd term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
S-PHYS-043Multivariate Statistics1515000Q2100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Master expertise.
    • Have acquired knowledge and a thorough understanding of specialist areas of physics in connection with mathematics and/or advanced laboratory practices required for these sectors.
  • Provide clear and accurate information.
    • Share their knowledge and findings clearly and back them up rationally to specialist and non-specialist audiences.
  • Collaborate and work in a team.
    • Have developed practical skills in physics through practical sessions in the laboratory and sessions during which they have worked individually and in groups.
  • Grow personally and professionally.
    • Have developed the skills that will enable them to continue to acquire knowledge independently.
  • Have a creative and rigorous scientific approach
    • Apply their knowledge, understanding and ability to solve problems in new or unfamiliar environments and in multidisciplinary contexts related to physical sciences.

Learning Outcomes of UE

At the end of the instruction, the students will be able to :
- Identify the multivariate analysis technique according to the nature of the statistical variables
- to apply the techniques of analysis in principal components, analysis of the (multiple) correspondences and the automatic classification in the statistical treatment of multidimensional sets of data
- to use a software of multidimensional statistical analysis

Content of UE

- Singular values decomposition
- Principal components analysis
- (Multiple) correspondence analysis
- Techniques of classification (k-means, hierachical clustering)
- Support vector machines

Prior Experience

- Uni- and bivariate basic statistics
- Hypothesis tests
- Basic matrix algebra

Type of Assessment for UE in Q2

  • Presentation and/or works

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

  • Oral examination

Q3 UE Assessment Comments

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
S-PHYS-043
  • Cours magistraux
  • Travaux pratiques
  • Projet sur ordinateur

Mode of delivery

AAMode of delivery
S-PHYS-043
  • Face to face

Required Reading

AA
S-PHYS-043

Required Learning Resources/Tools

AARequired Learning Resources/Tools
S-PHYS-043Not applicable

Recommended Reading

AA
S-PHYS-043

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
S-PHYS-043Not applicable

Other Recommended Reading

AAOther Recommended Reading
S-PHYS-043Statistique Exploratoire Multidimensionnelle - L. Lebart, M. Piron and A. Morineau - Dunod - 2006

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
S-PHYS-043Unauthorized
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 02/05/2019
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Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be