Volume 15, Number 2
Data Mining for Benford’s Law in Ancient Roman Coins
Authors
Akhilesh Warty and Eugene Pinsky, Boston University, USA
Abstract
This study examines the application of data mining techniques to analyze ancient Roman coin datasets and investigate the extent to which Benford’s Law is exhibited in the numerical values of the coins. Ben- ford’s Law predicts the frequency distribution of the first digits in naturally occurring datasets, and its applicability has been demonstrated across diverse fields. This research aims to explore whether ancient Roman coin values conform to this mathematical phenomenon, providing insights into the au- thenticity and naturalness of the data. By employing data mining methods, we analyze the leading digit distribution in a comprehensive dataset of ancient Roman coins. Additionally, we investigate trends and features within the dataset, such as coin composition, weight and diameter. The findings of this study contribute to the broader understanding of historical numismatic data and the relevance of Benford’s Law in historical datasets.
Keywords
Numismatics, Coin Classification, Benford’s Law, Data Mining.