When small data beats big data

Julian Faraway, Nicole Augustin

Research output: Contribution to journalArticlepeer-review

Abstract

Small data is sometimes preferable to big data. A high quality small sample can produce superior inferences to a low quality large sample. Data has acquisition, computation and privacy costs which require costs to be balanced against benefits. Statistical inference works well on small data but not so well on large data. Sometimes aggregation into small datasets is better than large individual-level data. Small data is a better starting point for teaching of Statistics.
Original languageEnglish
Pages (from-to)142-145
Number of pages4
JournalStatistics and Probability Letters
Volume136
Early online date17 Feb 2018
DOIs
Publication statusPublished - 1 May 2018

Keywords

  • Big data
  • Small data

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