Statistics and data science in history
- UE code LHISB323
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Schedule
30Quarter 1 + Quarter 2
- ECTS Credits 3
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Language
Français
- Teacher
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.
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.
Partie 1 – Statistiques appliquées à l'histoire
Partie 2 – Sciences des données
Examen oral, avec travail à préparer à l'avance.
Training | Study programme | Block | Credits | Mandatory |
---|---|---|---|---|
Bachelier en histoire | Standard | 0 | 3 | |
Bachelier en histoire | Standard | 3 | 3 |