course-details-portlet

HIKU8863 - Quantitative Methods for Historians

About

Examination arrangement

Examination arrangement: Home examination
Grade: Passed/Failed

Evaluation form Weighting Duration Examination aids Grade deviation
Home examination 100/100

Course content

The onset of big data has revolutionised how governments and the business sector make decisions. Likewise, the increasing availability of historical quantitative information provides an excellent opportunity to fully exploit the analysis of large datasets to expand our knowledge of the past.
This course provides an in-depth introduction to quantitative methods, covering some of the techniques most widely used in research in the historical and social sciences. Combining lectures and computer practicals, this hands-on course shows how to apply quantitative methods to historical information keeping statistical theory and mathematics to a minimum. The goal is to provide students with the tools to critically engage with the literature relying on quantitative methods and to be able to conduct original research using those tools either in academia, the public or the business sector. In the process, students will master Stata, a statistical software widely used by practitioners in many different fields.

Please note that if students plan to include this course in their coursework component, it must be preapproved by the relevant head of the study/PhD programme in cooperation with their supervisor.

Learning outcome

A candidate who satisfactorily passes the course will be able to:

- critically engage with studies relying on quantitative methods,
- conduct original research using those tools either in academia, the public or the business sector,
- master Stata, a statistical software widely used by practitioners in many different fields and available to NTNU students and faculty.

Learning methods and activities

30 hours: 10 three-hour sessions (one-week intencive course).
Each session combines lecturing (aprox. 1 hour) with computer practicals (aprox. 2 hours).

Every session combines lectures and computer practicals using Stata. This is an eminently hands-on course which keeps statistical theory and mathematics to a minimum. Students will learn by applying the different concepts to real data used by historians. Further information will be provided at the beginning of the course.

Compulsory assignments

  • Participation
  • 10 approved exercises

Further on evaluation

Compulsory attendance and compulsory session assignments (10 in total). Additionally, PhD students will require passing a take-home exam at the end of the course. A set of readings will also be assigned in preparation for the course.


Total workload of the course:

Preliminary readings + 30 hours teaching + 10 assignments + Take home exam

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Required previous knowledge

BA in History or equivalent. Admission to a relevant study programme is required.

Course materials

Course materials and assignments will be provided during the course.

Credit reductions

Course code Reduction From To
HIKU8862 7.5 01.09.2019
More on the course

No

Facts

Version: 1
Credits:  10.0 SP
Study level: Doctoral degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

Language of instruction: English

Location: Trondheim

Subject area(s)
  • European studies
  • European Studies
  • Archaeology
  • Geography
  • History
  • The Humanities
  • Sociology
  • Political Science
Contact information
Course coordinator:

Department with academic responsibility
Faculty of Humanities

Phone:

Examination

Examination arrangement: Home examination

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD Home examination 100/100
Room Building Number of candidates
Spring UTS Home examination 100/100
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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