Data analysis methodology

lfsm1301  2025-2026  Louvain-la-Neuve

Data analysis methodology
The version you’re consulting is not final. This course description may change. The final version will be published on 1st June.
4.00 credits
22.5 h + 22.5 h
Q2
Language
French
Prerequisites

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
  • Interpret qualitative and quantitative data 
  • Presenting data (table, graph, figure, etc.) 
  • Descriptive statistics 
  • Probabilities (including sample - population), inferences and statistical modelling 
  • Difference between causality and correlation 
  • Use of SPSS software 
  • Notions of reliability, validity, repeatability and reproducibility 
  • Thematic qualitative analysis 
Learning outcomes

At the end of this learning unit, the student is able to :

  • Describe and justify the relevance of data analysis methods (qualitative or quantitative) used in motor sciences (6.1 kiné) / (2.3. Master EP) 
  • Carry out relevant data analysis (6.1, 6.2 Kiné/2.3 EP) 
  • Analyse and interpret results to the point of arguing critically (2.3, 24 Master EP) 
  • Identify bias in a scientific article using appropriate scales (6.3 Kiné - 2.4 EP) 
  • Apply different statistical tests with relevance (6.2, 6.3 Kiné/2.3. EP) 
 
Other information
This course is strictly reserved for FSM students. It is not open to other UCLouvain students.
Faculty or entity
> FSM


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Motor Skills: General
MOTR2M
4
Master [120] in Motor Skills: Physical Education
EDPH2M
4
Bachelor in Physiotherapy and Rehabilitation
KINE1BA
4
LKNR1201
Master [120] of Education, Section 4 : Physical Education
EDPH2M4
4