Economics at your fingertips  

When small data beats big data

Julian J. Faraway and Nicole H. Augustin

Statistics & Probability Letters, 2018, vol. 136, issue C, 142-145

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.

Keywords: Big data; Small data (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2018-08-04
Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:142-145