Statistics and data science in history [LHISB323]

Learning outcomes

• Se former à la pensée critique et au raisonnement scientifique.
• Développer des savoirs complémentaires à l’Histoire.
• Maîtriser, au moins de façon passive, des approches quantitatives novatrices dans le domaine des études historiques.
• Acquérir les techniques d’analyse et d’interprétation des sources historiques, ainsi qu’une conscience réflexive et critique dans la pratique de la démarche historique.
• S’initier à la mise en œuvre d’une question de recherche en Histoire et maîtriser les outils et méthodes de travail propres à la discipline.

Objectives

Part 1 - Statistics applied to history


Part 2 - Data science

    Understand the basic principles and scientific contribution of new methods of quantitative analysis in History.
    Master the basic concepts of network analysis.
    Master the computer tools of network analysis (spreadsheet and software).
    Demonstrate a critical approach to analysis and interpretation of results.

Content

This course is divided into two parts: 'Statistics applied to history' (15 hrs, taught by Isabelle Parmentier) and 'Data science' (15 hrs, taught by Nicolas Ruffini-Ronzani).

Part 1 - Statistics applied to history


Part 2 - Data science

Without excluding more traditional approaches, new methods of numerical analysis now make it possible to carry out comprehensive and in-depth quantitative studies of vast bodies of documentation. The course aims to provide an introduction to these new approaches, demonstrating their usefulness to historians, whatever their preferred period. It will be divided into two parts: 1) In the first, more theoretical, part, an overview will be given of the methods used to analyse large documentary corpora and the way in which these approaches influence historical practice (text mining, stylometry, semantic analysis, etc.); 2) In the second, more practical, part, the focus will be on network analysis. After a presentation of the main concepts of this discipline, students will be introduced to the tools of network analysis (spreadsheet and software) based on case studies of historical sources.