When small data beats big data

Julian Faraway, Nicole Augustin

Research output: Contribution to journalArticlepeer-review

52 Citations (SciVal)
54 Downloads (Pure)


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 & Probability Letters
Early online date17 Feb 2018
Publication statusPublished - 1 May 2018


  • Big data
  • Small data

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability


Dive into the research topics of 'When small data beats big data'. Together they form a unique fingerprint.

Cite this