Quantitative methods for historical text analysis offer exciting opportunities for researchers interested in gaining new insights into long studied texts. However, the methodological underpinnings of these methods remains under-explored. In the first part of the talk I will show and discuss, through the use of a case study, the (non-)effect the OCR process has on a range of quantitative text analyses. In the second part of the talk, I will present a novel and totally unsupervised OCR post-correction method on the same dataset, as well as its most recent evolution on a highly-inflected language, Finnish.