I'm about to graduate and as most of my mates at university, I don't know what the heck I'm going to focus on. Lately I've developed an interest in programming and data science in particular and I've been wondering if there is a way to mix both data science and historical research together. They have in common the use of statistical data as a source. But during all semestres I've been studying, I haven't had any opportunity to research using statistical sources. The only time I did it was on a summer investigation on trade between Chile and Japan between 1934-1938 and boy, I was clueless about how to use all that data. The only guidance I was given was on historical context and bibliography, but nothing on statistical analysis.
Now, I remember reading some books that used or mentioned stadistical data to draw conclusions. Most were on economic history and, correct me if I'm wrong, but I recall Darton mentioning studies on medieval culture and concepts by using stadistical data derived from medieval literature. This was in his book titled "The Great Cat Massacre". But that's all.
I'm considering taking a course on social stadistics that the Sociology faculty is imparting in my university as I can't take any pure stadistic postgrade as they all require engineering or mathematical background. I can still learn the more technical side of data analysis by myself, but I'm unsure of how to apply it to historical studies. Any ideas?
Heres a TLDR round of questions:
Has stadistical data been used in recent Historical research? Where? How? Whom?
How is stadistics commonly used for research? Is there any advantage on using these kind of sources?
Has there been any discussion on methodology regarding the use of statistical sources?
What's your opinion on the possibility on combining data analysis and history? Is there any precedent for this?
Thanks in advance for any insight. I trully admire this community for the great effort you show when answering queries :)
The most interesting work in this field, in my view, is in the area of computational history. Check out the work of these folks, for example. They are applying serious statistical models derived from evolutionary biology to information about the development and evolution of scientific communities.
As for whether this stuff is common: no. There are many reasons for this, but largely historians are suspicious of "cliometrics" and "cliodynamics" in general. It has typically not been very popular and there are very few "success stories," e.g., historical insights/arguments that were developed by the use of quantitative measures that were surprising and accepted by the broader community. Part of this difficulty is that most historians do not have sufficient technical knowledge to do this kind of work (and are not interested in acquiring it). Part of this is a methodological disagreement that is very deep (most historians are, at their heart, qualitative empirical humanists).
But if you search for those terms (cliometrics, cliodynamics) you can find more information. People have been looking at this sort of thing for a long time. It is not especially popular amongst historians today for better or worse.