This course will provide students with a set of skills to apply quantitative methods to diverse types of data in order to address sociological issues. The students will learn to use the statistical language R. They do not need a strong mathematical, statistical, or computing background to succeed in this course.
Topics of lectures: Data visualizations / Describing data : summary statistics, useful distributions and how to use them / Data are never given: controlled experiments vs. observational studies vs. big data ; data management; creating databases from documents; sampling; questionnaire surveys / Beyond description: testing for the independence of two categorical variables; comparing means and testing for their difference / Describing and modeling data: correlation, linear models
Martin ARANGUREN,Sophia NOEL
Séminaire
English
Autumn 2024-2025
The evaluation of this course will be based on exercises (25%) and a final exam (75%) that will aim not to test the students' memory (course notes will be allowed) but their understanding of the methods and the ability to apply them in actual cases of quantitative research in the social sciences. For example, the test might require to sketch a research design, to critically assess data, to comment on a visualization, to find an error in an R script, etc.
Howell, D., Méthodes statistiques en sciences humaines (2e éd.), de Boeck supérieur, 2008