Méthodes quantitatives en sciences sociales : analyses causales, factorielles et typologies

Teacher(s)

Bocquier Philippe;

Language

French

Content

LDEMO2047 provides a solid introduction to quantitative methods in the social sciences. At the end of this course, students will be able to 

• to acquire mastery of the tools of bivariate and multivariate quantitative data analysis.
• use single and multiple regression methods and some applications of generalized linear models 
• understand and be able to use factorial analysis and classification techniques 
• to be autonomous in the use of the R software.

Topics covered:

• Univariate analysis (reminders): to describe the data.
• Chi-square test, relative risks, odds ratios: to analyze jointly two qualitative variables.
• T-Test, F-test and ANOVA: to test the relationships between a qualitative and a quantitative variable. 
• Correlations, linear regression: to analyze jointly two quantitative variables 
• Factorial analyses: to construct indicators or identify 'latent' dimensions of all the variables analysed.
• Classification methods: to identify clusters of units or to develop typologies.
• Multiple linear regression and the generalized linear model: to predict the value of a dependent variable, and identify its determinants.

Teaching methods

The course is structured around lectures and practical work (see programme on Moodle). Participation in courses and partical sessions is essential. It is necessary to read chapters from the curriculum beforehand.

Evaluation methods

• Three exercises associated with the practical work given during the first semester are evaluated and correspond to 30% (6/20) of the final grade.
• The final evaluation is based on a written exam given during the semester, which corresponds to 70% (14/20) of the final grade.
• In the event of failure in the 1st session, assessment is based on the exercises associated with the practical work (marked out of 6/20) and on the September examination (marked out of 14/20).

PLEASE NOTE: The use of artificial intelligence is not prohibited, but must comply with the rules set out in the ESPO faculty note on the subject, which is available on its intranet site for students (http://uclouvain.be/consignes-chatgpt) 

Online resources

Logiciel R: https://www.r-project.org/
Inferface Rstudio: https://www.rstudio.com/

Bibliography

G. Masuy-Stroobant and R. Costa, editors. Analyser les données en sciences sociales : De la préparation des données à l'analyse multivariée. P.I.E. Peter Lang, 2013.
D.C. Howell, V. Yzerbyt, Y. Bestgen, and M. Rogier. Méthodes statistiques en sciences humaines. Série Internationale. De Boeck Supérieur, 2008.
 

Teaching materials

• G. Masuy-Stroobant and R. Costa, editors. Analyser les données en sciences sociales : De la préparation des données à l'analyse multivariée. P.I.E. Peter Lang, 2013. Disponible en bibliothèque et sur Moodle

Faculty or entity

> PSAD