Stochastic aspects of one-dimensional discrete dynamical systems: Benford’s law

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Abstract
Benford’s law owes its discovery to the “Grubby Pages Hypothesis,” a 19th century observation made by Simon Newcomb that the beginning pages of logarithm books were grubbier than the last few pages, implying that scientists referenced the values toward the front of the books more frequently. If a data set satisfies Benford’s law, then it’s significant digits will have a logarithmic distribution, which favors smaller significant digits. In this article we demonstrate two ways of creating discrete one-dimensional dynamical systems that satisfy Benford’s law. We also develop a numerical simulation methodology that we use to study dynamical systems when analytical results are not readily available.

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