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‘Bad’ distributions of good data: unusual statistics of structural databases

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Abstract

Distributions of data taken from crystal structure databases, display unusual statistical properties like non-Gaussian shape, polymodality, and heavy tails. These features, typical for statistics of numerical data in social systems, appear in bigger sets (from hundreds to many thousand points) of database-originated parameters. The non-classic statistics of physical data collected through many years reflects a strong impact of social factors (financial support, exchange of information, competition, etc.) on a research activity. The values of some definite structural parameter, determined (and deposited to a database) by different authors, generally are neither independent nor random; their handling by common statistical tools may result in incorrect conclusions and wrong predictions. These statements are illustrated by several sets of reliable structural data whose statistics looks ‘bad,’ or inconclusive, in contemporary structural chemistry.

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Acknowledgments

The author is indebted to Viktor Rybakov and Vladimir Chernyshov for their kind help with numerical data and stimulating discussions.

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Authors and Affiliations

  1. Department of Chemistry, Lomonosov Moscow State University, 1 Vorobyovy Gory, bld. 3, Moscow, 117992, Russian Federation

    Yuri L. Slovokhotov

  2. Institute of Organoelement Compounds, Russian Academy of Sciences, 28 Vavilov St., Moscow, 119991, Russian Federation

    Yuri L. Slovokhotov

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  1. Yuri L. Slovokhotov
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Correspondence to Yuri L. Slovokhotov.

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Dedicated to the memory of Prof. Oleg Valeryevich Shishkin.

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Slovokhotov, Y.L. ‘Bad’ distributions of good data: unusual statistics of structural databases. Struct Chem 27, 389–400 (2016). https://doi.org/10.1007/s11224-015-0716-3

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  • DOI: https://doi.org/10.1007/s11224-015-0716-3

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