Study programme 2021-2022Français
Multivariate Inferential Statistics
Programme component of Bachelor's in Psychology and Education: General à la Faculty of Psychology and Education

CodeTypeHead of UE Department’s
contact details
Teacher(s)
UP-B3-BAGENE-011-MCompulsory UEHUET KathyP362 - Métrologie et Sciences du langage
  • HUET Kathy

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français151500044.002nd term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
P-SMSL-060Multivariate Inferential Statistics: Procedures155000Q2
P-SMSL-230Multivariate Inferential Statistics: Software Problems010000Q2

Overall mark : the assessments of each AA result in an overall mark for the UE.
Programme component
Prérequis
Corequis

Objectives of Programme's Learning Outcomes

  • Understand the theoretical and methodological fundamentals in psychology and educational sciences to analyse a situation involving these disciplines
    • Describe the principles of methodological approaches (objectives, methods, techniques and tools) to understand and explain the functioning of individuals, groups and organisations
  • Provide clear, accurate, and reasoned information
    • Summarise the contributions of different sources to justify an opinion or decision
    • Write bibliographic references and results of statistical analysis in a standardised way (according to APA standards)
  • Understand the fundamentals related to the scientific approach in psychology or educational sciences
    • Identify and explain the main methods (including limitations) specific to the scientific process

Learning Outcomes of UE

The student will be able to reconstruct the reasoning having proceeded to the construction of the procedures / to select (the) procedure (s) adequate to the treatment of a given problem  / to perceive the limitations of the inferences built from a statistical treatment / to proceed to the treatment of concrete data by means of the procedures being the object of the lessons with help either of the calculator or the proposed statistical software.

Content of UE

Statistical Tests of hypothesis: parametric analyses of variance (simple, for completely nested device, in two-crossed criteria), analyzes the covariance, nonparametric analyses of variance (Friedman, L of Page, Kruskal-Wallis).
Analysis of the link between variables: notion of correlation, multiple correlation, partial correlation, not linear correlation, nonparametric correlation.
Data processing by means of statistical treatment software.

Prior Experience

Méthodologie de l'expérimentation (bloc2)
Statistique I (bloc1)

Type of Assessment for UE in Q1

  • Written examination
  • Graded tests

Q1 UE Assessment Comments

AA1 (Q1) : Written examination about theory (65%) and exercices (45%) = 80% UP

Type of Assessment for UE in Q2

  • Written examination
  • Graded tests
  • eTest

Method of calculating the overall mark for the Q2 UE assessment

Note UE = 80% AA1 : written exam : theory (65%) + ex (35%) + 20% AA2 : project report

Q2 UE Assessment Comments

AA1 : Written exam in session comprising two parts: a part on the theory (65%) and a part on the exercises (35%) = 80% UE
AA2 : based on project = 20% UE.  Groups of 2 students are established by students themselves via the platform Moodle following a schedule specified at the beginning of course. Every student who not respecte the term of registration will be considered as absente for this AA.

Type of Assessment for UE in Q3

  • Written examination
  • Graded tests
  • eTest

Method of calculating the overall mark for the Q3 UE assessment

Note UE = 80% AA1 (written exam : theory (65%) + ex (35%)) + 20% AA2

Q3 UE Assessment Comments

Note of AA1 obtained at Q1 is not maintained.
Note of AA2 obtained at Q1 is maintained if > 10/20

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
P-SMSL-060
  • Cours magistraux
  • Exercices dirigés
  • Démonstrations
P-SMSL-230
  • Exercices dirigés
  • Utilisation de logiciels
  • Démonstrations

Mode of delivery

AAMode of delivery
P-SMSL-060
  • Face to face
  • Mixed
P-SMSL-230
  • Face to face
  • Mixed

Required Reading

AA
P-SMSL-060
P-SMSL-230

Required Learning Resources/Tools

AARequired Learning Resources/Tools
P-SMSL-060Available from Moodle :
Lessons notes ;
Collection of solved exercises and to solve ;
Copies of slides
videos
P-SMSL-230Learning site
Copies of slides
Videos

Recommended Reading

AA
P-SMSL-060
P-SMSL-230

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
P-SMSL-060Laveault, D. & Grégoire, J. (2002). Introduction aux théories des tests en psychologie et en éducation . Bruxelles: De Boeck
Bonniol, Jean-Jacques, Vial, Michel, Les modèles de l'évaluation (textes fondateurs avec commentaires), coll. Pédagogie, De Boeck université, Paris, Bruxelles, 1997 (ISBN 2-8041-2636-6)
Rust J. and Golombok S., Modern Psychometrics, The science of Psychological Assessment, Routledge, London, 1989
Pedhazur, E., Pedhazur Schmelkin, L., Measurement, design and analysis: an intergrated approach, Hillsdale New Jersey, Lawrence Erlbaum Associates, 1991.
P-SMSL-230Not applicable

Other Recommended Reading

AAOther Recommended Reading
P-SMSL-060Laveault, D. & Grégoire, J. (2002). Introduction aux théories des tests en psychologie et en éducation . Bruxelles: De Boeck
Bonniol, Jean-Jacques, Vial, Michel, Les modèles de l'évaluation (textes fondateurs avec commentaires), coll. Pédagogie, De Boeck université, Paris, Bruxelles, 1997 (ISBN 2-8041-2636-6)
Rust J. and Golombok S., Modern Psychometrics, The science of Psychological Assessment, Routledge, London, 1989
Pedhazur, E., Pedhazur Schmelkin, L., Measurement, design and analysis: an intergrated approach, Hillsdale New Jersey, Lawrence Erlbaum Associates, 1991.
P-SMSL-230Not applicable
(*) 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 dernière mise à jour de la fiche ECTS par l'enseignant : 10/05/2021
Date de dernière génération automatique de la page : 06/05/2022
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