CHANCE 35(2), pp. 11-15.
ISSN/ISBN: Not available at this time. DOI: 10.1080/09332480.2022.2066410
Abstract: John von Neumann emphasized the importance of models in science. In this paper we compare the efficacy and ease of use of two quite different models, Benford’s Law and a version of Zipf’s Law to help us to understand the data that have rained upon us from the COVID pandemic. We conclude that Zipf’s Law seems to have much to offer. We recommend it and urge others to try it out. Benford’s Law, not so much.
Bibtex:
@article{,
author = {Paul Velleman and Howard Wainer},
title = {Exploring COVID Data with Benford’s and Zip’s Laws},
journal = {CHANCE},
volume = {35},
number = {2},
pages = {11-15},
year = {2022},
publisher = {Taylor & Francis},
doi = {10.1080/09332480.2022.2066410},
}
Reference Type: Journal Article
Subject Area(s): Medical Sciences, Statistics