Lineaments of territory

Quantitative surveys. Social Science Toolkit
Monday 16 September 2024 Monday 16 September 2024
From 3 to 6 PM
data analysis
ENS, salle de conférence du centre de science des données

45 rue d'Ulm
75005 Paris

48.8418371, 2.3440403

First session of the course "Enquêtes quantitatives. Boîte à outils pour sciences sociales", given by Theo Boulakia.

One day you'll want to make a map. A simple one: the layout of a hamlet, a crime scene, a sailor's journey from the Marquesas Islands to Moscow. You'll have three types of tools at your disposal: pencil and paper, specialized software or a general-purpose data science language. We'll explore the third possibility, and see how a few lines of code (R, Python or Julia) can map a bewildering number of phenomena. In the down-to-earth part of the course, we'll cover the following topics. Where can I find structured geographic information? How are spatial data represented (vector and raster models)? What transformations can be applied? What tools (languages, software, packages) can be used to manipulate them? Three books, three surveys - in Mongolia, Jamaica and France - will serve as red threads. They will raise no less interesting questions. How can we represent the territories we live in? Are maps just wallpaper? How do we map the ephemeral, the clandestine?

Monday 16 September 2024
data analysis

Quantitative surveys. Social Science Toolkit

S1 2024-2025.

Data analysis course in social sciences, delivered by Théo Boulakia. The sessions take place on Mondays, from 3 p.m. to 6 p.m., in the conference room of the Data Science Center (ENS-PSL, 45 rue d'Ulm, at the top of stairs B or C).

Goals of the course: This course offers an introduction to various quantitative methods based on social science surveys. Each session is organized around the meeting between a question (sociological, anthropological, historiographical), data and a method: cartography, dimensionality reduction, partitioning, sequence analysis, textual analysis, Bayesian statistics. The objective of the course is to acquire a schematic understanding of the implementation of these methods, their merits and their limitations. How to represent spatial data and temporal sequences? What do Bayesian statistics provide that the frequentist approach lacks? How to analyze the morpho-synthactic properties of a text? How to go from a large number of variables to a small number of classes? These questions will arise in context, in a dynamic of adjustment between data, method and research question (an investigation dynamic). Programming questions will be covered only in broad terms, no experience in this area is required.

Validation: Submit a four-page document applying one of the methods discovered in progress to your own data: presentation of the data, interest of the method, implementation and interpretation. People without programming experience will be assisted with implementation.

Registration : theo.boulakia [a]