Making Economic History Count
This information is for the 2018/19 session.
Dr Jordan Claridge
This course is available on the BSc in Economic History. This course is not available as an outside option nor to General Course students.
This course is very strongly recommended for all first year Economic History students.
This course provides students a brief, non-technical introduction to the quantitative methods that economic historians use to understand the past. It assumes no prior statistical knowledge or experience. It will teach students basic statistics (descriptive statistics and inferential statistics) and how to implement and visualise these statistics with Excel. These skills will be essential for the independent research projects conducted in the second and third year and are highly desired skills on the job market. In addition, it will introduce students to regression analysis and teach them to interpret regression tables. Regression analysis is a very common methodology employed in the economic history and economics literature, so understanding how to interpret regressions will allow students to engage with readings for other economics and economic history courses at a higher level. All first year Economic History students are very strongly encouraged to take this course.
10 hours of lectures and 10 hours of classes in the MT.
Some of the classes will take the form of computer based workshops.
The formative coursework will consist of weekly exercises to give students practise with Excel and the methods being taught in the lecture. There will be a formative take home exam over Christmas Break (due week 2 of Lent Term) to test students' knowledge of the material.
Feinstein, Charles and Mark Thomas, Making History Count: A Primer in Quantitative Methods for Historians (Cambridge, 2002).
Hudson, Pat and Mina Ishizu, History by Numbers (London, 2016).
There is no summative assessment for this course.
Department: Economic History
Total students 2017/18: 53
Average class size 2017/18: 16
Capped 2017/18: No
Lecture capture used 2017/18: Yes (MT)
Value: Non-credit bearing
- Problem solving
- Application of information skills
- Application of numeracy skills
- Specialist skills