liepr1026  2020-2021  Louvain-la-Neuve

Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
3 credits
15.0 h + 15.0 h

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
The course comprises theoretical lectures and exercise sessions: 1. Brief recall on one- and two-dimensional descriptive statistics 2. Inferential statistics: populations and samples, probabilities, variables, theoretical distributions, confidence intervals (means, variance, proportion), hypothesis testing based on sample means (Student t-test, analysis of variance, analysis of covariance, multiple comparisons), proportions (chi square, phi, contingency), correlations/regressions (significance, comparison, linearity), adjustment tests (chi square, KS), non-parametric tests (comparison of independant and dependant groups). 3. Application to capacity tests: classification of tests, quality of tests, validity and reproducibility.

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

1 At the end of the course the successful student will be able to use the techniques of inferential statistics within the framework of his/her research. The course focuses on the most frequently used statistical methods. The underlying mathematical developments are limited to a strict minimum and replaced by intuitive reasoning and concrete examples, especially via practical exercise sessions.

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
This course includes lectures and exercises. It contains a brief overview of the concepts of one- and two-dimensional descriptive statistics as seen in thecourse of 11 BAC "Comprehension et traitement de données". It focuses mainly on the basic issues of statistical inference: population and sample probabilities, random variables, distribution theory, confidence intervals (mean, proportion), hypothesis tests related to means (student t, analysis of variance), proportions (1 or 2 proportion test, chi-square test), correlation/regression study (regression straight line calculation, slope test), adjustment tests (chi-square, Shapiro-Wilks), some non-parametric tests (comparison of independent and dependent groups), repeated measurement ANOVA.
Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Lectures and supervised exercises. The modalities foreseen will evolve according to the health situation.
Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Other information
Pre-requisite: Comprehension et traitement de données (LIEPR1003)
Evaluation: Written
Support : power point
Supervision: Titular professors and teaching assistants
Others: Exercise sessions + solutions to problems
Online resources
Site Moodle:
Faculty or entity

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

Title of the programme
Bachelor in Physiotherapy and Rehabilitation

Master [120] in Motor Skills: General

Master [120] in Motor Skills: Physical Education