Youden's demon is Sylvester's problem

Abstract If four people with Gaussian‐distributed heights stand at Gaussian positions on the plane, the probability that there are exactly two people whose height is above the average of the four is exactly the same as the probability that they stand in convex position; both probabilities are . We show that this is a special case of a more general phenomenon: The problem of determining the position of the mean among the order statistics of Gaussian random points on the real line (Youden's demon problem) is the same as a natural generalization of Sylvester's four point problem to Gaussian points in . Our main tool is the observation that the Gale dual of independent samples in itself can be taken to be a set of independent points (translated to have barycenter at the origin) when the distribution of the points is Gaussian.

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Publication Details

Journal
Mathematika
Published
2025-02-18
DOI
https://doi.org/10.1112/mtk.70015
Citations
2
Primary Topic
Mathematics and Applications
Type
article
Field-Weighted Citation Impact
8.18

Funders

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article

Youden's demon is Sylvester's problem

Wesley Pegden, Florian Frick, Andrew Newman
2 citations
Mathematika
Mathematics and Applications
8.18
article

Youden's demon is Sylvester's problem

Wesley Pegden, Florian Frick, Andrew Newman
article en
2 citations

Abstract

Abstract If four people with Gaussian‐distributed heights stand at Gaussian positions on the plane, the probability that there are exactly two people whose height is above the average of the four is exactly the same as the probability that they stand in convex position; both probabilities are . We show that this is a special case of a more general phenomenon: The problem of determining the position of the mean among the order statistics of Gaussian random points on the real line (Youden's demon problem) is the same as a natural generalization of Sylvester's four point problem to Gaussian points in . Our main tool is the observation that the Gale dual of independent samples in itself can be taken to be a set of independent points (translated to have barycenter at the origin) when the distribution of the points is Gaussian.

MathematikaVol. 71(2)
Carnegie Mellon University (US)
National Science Foundation
Openalex Percentile: Top 4%
Mathematics and Applications
8.18
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