This is the first of a series of articles about analysing text data. The statistical music historian might be interested in many sorts of text – from lists and catalogues through to complex ‘free format’ writing in tweets, record reviews, composer biographies, or encyclopedias. For these articles I will consider a dataset of song lyrics, taken from the LyricWiki website [since I wrote this post, LyricWiki has disappeared, although there are several other sources of song lyrics that could be used].
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Triangulation is a research technique that involves looking at the same thing from two different perspectives. In surveying, it enables positions and distances to be calculated by measuring angles from two locations. In the social sciences, it can increase the reliability of conclusions if they are found by two (or more) different methods. And in statistical historical musicology, looking for the same works or composers in two or more datasets can tell us a lot about the characteristics of the datasets, and about the works’ patterns of survival or dissemination. 
In what ways can statistical techniques be used to investigate topics in historical musicology? I think there are four main approaches – hypothesis testing, quantification, modelling and exploration. Their use depends on the topic, the data, and the type of question you are trying to answer.