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Biostatistics in public health : part I
Titulaire(s) du cours
Samuel Salvaggio (Coordonnateur)Crédits ECTS
5
Langue(s) d'enseignement
anglais
Contenu du cours
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A-Biostatistics: (S. Salvaggio)
Basic concepts and methods of statistics with illustrations from health sciences; descriptive statistics, graphical representations, probability, random variables, normal distribution, binomial distribution, and inferences (estimations and hypothesis testing including t-tests, chi-square tests, and Mc Nemar test).
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B-Data Management and analysis with R (S. Farag)
Introduction to the use of the statistical software R.
R studio, data entry, editing and organizing datasets, exploring datasets, manipulation of variables, graphical displays and data analysis.
Objectifs (et/ou acquis d'apprentissages spécifiques)
To provide an understanding of basic concepts in statistics and introduction to a statistical software package use for data processing and statistical analysis. Emphasizes applications in health sciences. The course fosters ability of students to select relevant analysis techniques, synthesize knowledge, and apply insights to address public health problems.
Méthodes d'enseignement et activités d'apprentissages
A- Biostatistics
The course consists of state of the art lectures, interactive case presentations, group discussions and practical exercises.
B- Data management and analysis with R
The course consists of practical exercises with real world data.
Références, bibliographie et lectures recommandées
See recommendations given during the lessons.
Contribution au profil d'enseignement
Contribution to
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SKILL 1. Applying a corpus of pluridisciplinary methodological knowledge to the analysis of various public health issues , specifically « Analyse data gathered using appropriate methods » and « Evaluate the quality and limits of the methods used to gather, save, analyse, and share research data »
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SKILL 3. Organising individual and collective work in collaboration with various partners, more specifically « Plan work in order to achieve results within the intended timeframe » and « Work as part of a team, with shared tasks and group dynamics »
Autres renseignements
Contacts
Samuel Salvaggio (samuel.salvaggio@ulb.be)
Campus
Erasme
Evaluation
Méthode(s) d'évaluation
- Travail personnel
- Examen écrit
Travail personnel
Examen écrit
Lectures in biostatistics: individual sitting exam
Data management and analysis with R: individual data analysis project
Construction de la note (en ce compris, la pondération des notes partielles)
80% sitting exam + 20% data analysis project
The mean score should be superior or equal to 10/20 overall to pass the Learning Unit at the 1st session.
Second session:
When the Learning Unit is not validated at the 1st session, the 2d session will include one examination regarding ONLY the failed activity part(s) (sitting exam and/or data analysis project).
Langue(s) d'évaluation
- anglais