The aim of this course is to provide research-oriented history students with a thorough introduction into statistics and quantitative research. As such, the course provides essential background to students working with quantitative historical data and allows students to engage with statistical results presented in the literature. The topics covered in the course are:
- Presenting and interpreting quantitative data (univariate analysis)
- Statistical hypotheses and correlations (bivariate analysis)
- Introduction into regression analysis (multivariate analysis)
In addition, the course emphasizes transparent management of data using the statistical software-package Stata (course-access will be provided).
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Researchers in economic and social history regularly work with quantitative data such as prices and wages or demographic data. To acquaint students with quantitative research, this course offers a thorough introduction of these methods, aimed at research master students interested in economic and social history. It focuses first on getting the basics rights; what is data, what types of data are there, what are the main uses and pitfalls? Then, working with one or two variables, it discusses how quantitative data can be used to describe and explore historical patterns, and to test theories about these patterns. Of course, the questions historians address often require the study of several variables or a detailed analysis of chronology. Regression analysis is an invaluable tool to use quantitative data for such questions. Accordingly, the final weeks of the course introduce students to regression analysis, allowing students to engage with quantitative literature in the field and providing a foundation for further in-depth study of regression analysis.
The course takes a hands-on-approach: There will be weekly lectures followed by lab hours wherein students work on assignments to practice the material using Stata. In addition, students learn to write do-files in Stata allowing full reproducibility of results, from the initial data to the final tables and graphs.
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