Duration
45h Th
Number of credits
| Master in psychology (120 ECTS) | 6 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
Students and researchers as well are often lost in front of their data. Most of the time, they simply don't know how to analyse the data or, worse, they do it in a wrong or ineficient way. The classes will give them a better understanding of statistics based on regression analysis. We will present analyses based on models comparison in the sake of a better understanding of the data.
Index: regression analysis with 1 continuous or categorical predictor, 2 continuous or categorical predictors, 2 predictors and the interaction (moderation), mediation analyses.
Learning outcomes of the learning unit
The aim is to enhance students' understanding of the domain as well as their ability to correctly analyse data. They should become "data analysers" more than statisticians.
Prerequisite knowledge and skills
Planned learning activities and teaching methods
Oral presentation by the teacher. Individual work (classes' preparation). Exercises and interpretation of results.
Usually, the class starts with an abstract of the material seen during the former session, Q-A from the students, resolution and comments of the exercises. These exercises are discussed either during the class or indivudualy prepared. This material will be available on the internet.
The specific teaching method could change depending on the number of students
Mode of delivery (face-to-face ; distance-learning)
Face-to-face with individual preparation.
Recommended or required readings
Mandatory: Judd, C. M., McClelland, G. H., Ryan, C. R., Muller, D., & Yzerbyt, V. (2eme Ed., 2018). L'analyse des données : une approche par comparaison de modèles. De Boeck, Bruxelles.
Non madatory: Hayes, A. F. (2018). Mediation, Moderation, and conditional process analysis. Guilford.
Assessment methods and criteria
At the end of some of the classes (those concerning chap 4 to 10; 10 min maximum duration),for 1 point: A very short question on the chapters presented and discussed during the class, generaly about a statistical output.
Exam in january / august : interpretation of statistical outputs but also Q on the chap from Judd et al. (2010)
The specific assessment method could change depending on the number of students
Work placement(s)
Organizational remarks
In order for the students to prepare the material, the class will be organize every two weeks. The calendar will be given during the first class.
Contacts
b.dardenne@uliege.be
Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session
Teaching methods implemented : distance-learning
Assessment subjects
Assessment methods
Contacts
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
Matière inchangée
Assessment methods
L'examen se déroulera à distance. Le jour et à l'heure de celui-ci, vous recevrez un email avec comme pièce jointe un fichier .doc à compléter. L'examen durera 1h et vous me renvoyez le fichier complété par email (b.dardenne@uliege.be). Après 1h d'examen, votre copie sera "tardive"... Le type de questions et les modalités de réponses seront identiques à la session de janvier. Les questions seront issues d'un pool et donc vous êtes susceptibles de recevoir des questions "uniques". Avec ce type d'examen, vous disposerez bien entendu de toutes les ressources à votre disposition (livres, dias du cours, internet, etc).