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 language | English |
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Pages (from-to) | 142-145 |
Number of pages | 4 |
Journal | Statistics & Probability Letters |
Volume | 136 |
Early online date | 17 Feb 2018 |
DOIs | |
Publication status | Published - 1 May 2018 |
Keywords
- Big data
- Small data
ASJC Scopus subject areas
- Statistics, Probability and Uncertainty
- Statistics and Probability
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Julian Faraway
- Department of Mathematical Sciences - Professor
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
Person: Research & Teaching