mmeth1322  2020-2021  Mons

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).
5 credits
30.0 h + 30.0 h
Q1
Teacher(s)
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.
Content
  • Reminders of basic statistical vocabulary and concepts.
  • Addressing a research question with quantitative data: the main steps.
  • Quantitative data : how are they produced, what are their strengths and weaknesses, where can they be found?
  • Preparation, description, visualization and critique of data before analysis.
  • Reminders of notions of inference, hypothesis testing, etc.
  • Univariate methods of analysis.
  • Analyze relationships between two variables: contingency tables, differences in means, linear correlations.
  • Methods of index construction.
  • Causal analysis and statistical models: single and multiple linear regression, logistic regression.
  • Introduction to principal component analysis and classification analysis.
  • Analysis of survey data with SPSS software.
Teaching methods

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

Lectures and practical work.
The course focuses on the development of data analysis skills. It has a strong practical component, through the manipulation of statistical software and the use of survey data to address research questions. 
The lectures are organized around the presentation of analytical methods, their conditions of use, and the interpretation of the results of these methods in the context of social and political science issues. The practical work aims to develop the use of a statistical analysis software for data preparation (recoding, data structuring, etc.), data description, and the implementation of more advanced methods. Students also practice data analysis to address research questions as part of personal research work.
Evaluation methods

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

January session
The evaluation is based on a practical work (50% of the final grade) and an oral examination (50% of the final grade). The oral examination focuses on the work and the material seen during the course (with possible data manipulation). The work is carried out during the four-month period, and supervised by the teachers.
September session
In the case of a second session, the student may pass both parts of the assessment, or keep the note of the practical work for the September session. The modalities are identical to the June session.
Other information
The data used in the course are from the European Social Survey (http://www.europeansocialsurvey.org/).
The analyses are carried out with the SPSS software, available on the computers of the computer rooms
Online resources
> https://www.europeansocialsurvey.org/
Relevant information can be placed on Student Corner.
Masuy-Stroobant G. et Costa R. (eds), 2013, Analyser les données en sciences sociales. De la préparation des données à l’analyse multivariée, Peter Lang, Bruxelles, 301 p. (Livre téléchargeable à l'adresse suivante : https://www.peterlang.com/downloadpdf/title/50872)
Bibliography
Teaching materials
  • Masuy-Stroobant G. et Costa R. (eds), 2013, Analyser les données en sciences sociales. De la préparation des données à l’analyse multivariée, Peter Lang, Bruxelles, 301 p.
  • Micro-données de l'enquête sociale européenne
  • Les diapositives du cours sont disponibles sur student corner.
Faculty or entity


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

Title of the programme
Sigle
Credits
Prerequisites
Aims
Bachelor in Political Sciences: General

Bachelor in Human and Social Sciences