The “Poisson” Distribution: History, Reenactments, Adaptations

James A. Hanley and Sahir Bhatnagar

The American Statistician, 2022, vol. 76, issue 4, 363-371

Abstract: Although it is a widely used—and misused—discrete distribution, textbooks tend to give the history of the Poisson distribution short shrift, typically deriving it in the abstract as a limiting case of a binomial. The biological and physical scientists who independently derived it using space and time considerations and used it in their work are seldom mentioned. Nor are the difficulties of applying it to counts involving human activities/behavior. We (a) sketch the early history of the Poisson distribution (b) illustrate principles of the Poisson distribution involving space and time using the original biological and physical applications, as well as modern multimedia reenactments of them, and (c) motivate count distributions accounting for extra-Poisson variation. The replayed historical applications can help today’s students, teachers and practitioners to see or hear what randomness looks or sounds like, to get practice in the practicalities of “counting statistics,” to distinguish situations where the pure Poisson distribution does and doesn’t hold—and to think about what one might do when it doesn’t.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00031305.2022.2046159 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:amstat:v:76:y:2022:i:4:p:363-371

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTAS20

DOI: 10.1080/00031305.2022.2046159

Access Statistics for this article

The American Statistician is currently edited by Eric Sampson

More articles in The American Statistician from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().