When small data beats big data

By Julian J. Faraway, Nicole H. Augustin. 2018

81 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence, Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e384fd9aa054ab9873e496f1c5ba8287f5670f64