2024-2025 / HIST0002-1

Historical statistics and computational methods applied to modern and contemporary history

Duration

45h Th

Number of credits

 Bachelor in history5 crédits 
 Master in history, research focus5 crédits 
 Master in history, teaching focus5 crédits 
 Master en histoire, à finalité spécialisée en transmission numérique des savoirs historiques (Pas organisé en 2024-2025)5 crédits 
 Master in history (60 ECTS)5 crédits 

Lecturer

Eric Geerkens

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

There are four parts to the course.
1. An introduction to the history of quantification and statitics and a presentation of some of the principles of historical criticism of quantitative data.
2. A presentation of the basic concepts of descriptive univariate statistics and of their usefulness for historical research: types of variables, central parameters, dispersion parameters, growth rates, index, graphic representation of data.
3. An introduction to bi(multi)variate statistics: temporal series (regression and linear correlation); distribution (contingency tables, interdependence); introduction to hypothesis testing; brief introduction to data analysis (factorial analysis). The presentation of each concept will be coupled with illustrations and concrete operations using simplified data (using Excel).
4. Students will be allocated a collection of readings giving an insight into the use of quantitative methods to respond to questions posed by historians based on recent historical work; they will be asked to present them orally.

Learning outcomes of the learning unit

By the end of the course, students will be able to :





  • Use desktop applications to process data (using Excel available via Office 365 as a database (filters, dynanmic cross-referenced tables); use of these same tools to process descriptive statistics) ;
  • Using descriptive statistics to summarise data ;
  • Identify the statistical methods enabling them to answer questions which historians may ask;
  • Understand the principles behind the most widely used historical statistical methods.

Prerequisite knowledge and skills

Planned learning activities and teaching methods

Mode of delivery (face to face, distance learning, hybrid learning)

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Course materials and recommended or required readings

Platform(s) used for course materials:
- MyULiège


Further information:

Students are asked to read: LEMERCIER, Claire and ZALC Claire, Méthodes quantitatives pour l'historien, Paris, La Découverte (coll. Repères), 2008, 120 pp.

Via MyULiège, they will also receive each week copies of Powerpoint slides shown in class. These slides are animated to support the attention and are also, on the same time, very complete ; bibliographical orientations are proposed in food-notes.

Exam(s) in session

January exam session

- In-person

written exam ( open-ended questions )

August-September exam session

- In-person

written exam ( open-ended questions )


Further information:

The exam (of each session) is written and is open book (course notes as well as computer files, but no connection to the web). It includes theory questions (which are actually comprehension questions) and exercises (mainly processing data).

The January written exam covers the material covered in Q1; its precise scope will be agreed with the students at the end of Q1. This exam is not dispensatory. It counts for 25% of the final grade; however, if the grade is < 10/20, it does not count towards the final grade.

Work placement(s)

Organisational remarks and main changes to the course

The personal laptops are obviously welcome. A small number of computers are available for students who do not have a laptop. 

Contacts

Eric Geerkens, professor Histoire économique et sociale quai Roosevelt, 1B (Bât. A4) 4000 Liège Belgium
Tel. ULg : +32 4 3665359 Mail : e.geerkens@uliege.be 

Association of one or more MOOCs

Items online

Online Notes
Notes are available on MyULg.