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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Computing in Science...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Computing in Science & Engineering
Article . 2001 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Poisson distributions

Authors: W.J. Thompson;

Poisson distributions

Abstract

Scientists and engineers often use Poisson's probability distribution to characterize the statistics of rare events whose average number is small. Using it correctly is crucial if we are to validate claims of discovery of new phenomena, such as a new fundamental particle (few candidate collision events among millions), a remote galaxy (few photons in the telescope among the billions emitted), or brain damage from using cell phones (few tumors among millions of users). In risk assessment, such as estimating the chance of dying from a horse kick if you're in the Prussian army or from suicide (two of its early uses), it plays a crucial role, which should interest actuaries as well as morticians. The author has noticed that the Poisson distribution is often misunderstood and misapplied, so he describes some of its interesting and relevant properties. He emphasizes visualizing what's happening in the mathematics by using Mathematica.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Average
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