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big data paradox: a standalone construct

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big dataparadox1 CONSTRUCTBig data paradoxMENG · SURVEY METHODOLOGY

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Survey methodology

the result that a huge nonrandom sample can carry less information than a small random one, because slight selection correlation dominates as population size grows.

In survey methodology, big data paradox refers to the result that a huge nonrandom sample can carry less information than a small random one, because slight selection correlation dominates as population size grows. This meaning comes from Meng (2018) in The Annals of Applied Statistics.[1]

Unit
Recovery means
Measured by

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big data1 fields · 1 citationsanchor · a standalone constructcarry1 fields · 1 citationsanchor · a standalone constructcorrelation4 fields · 4 citationsjingle · one word, four constructs

References

  1. Meng, X. (2018). Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election. The Annals of Applied Statistics, 12(2), 685-726. https://doi.org/10.1214/18-aoas1161sf

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