Imperial College London
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ProfessorDavidHand

Faculty of Natural Sciences, Department of Mathematics

Senior Research Investigator
 
 
 
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Contact

 

+44 (0)20 7594 2843d.j.hand CV

 
 
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Assistant

 

Mrs Agnieszka Damasiewicz Niccolai +44 (0)20 7594 2843

 
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Location

 

547Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Vichi:2019:10.3233/sji-190526,
author = {Vichi, M and Hand, DJ},
doi = {10.3233/sji-190526},
journal = {Statistical Journal of the IAOS},
pages = {605--613},
title = {Trusted smart statistics: The challenge of extracting usable aggregate information from new data sources},
url = {http://dx.doi.org/10.3233/sji-190526},
volume = {35},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Recent years have seen dramatic changes in sources of data, amounts of data, availability of data, frequency of data, and types of data. Along with advances in data analytic technology these changes have opened up huge possibilities for improving the information content and timeliness of official statistics. in this paper we characterise such “smart statistics”, examining their potential benefits and the obstacles that must be overcome if they are to be trusted and relied upon. In particular, we list eight specific recommendations which we believe producers of smart statistics should adhere to if the full potential for economic and social benefit is to be achieved.
AU  - Vichi,M
AU  - Hand,DJ
DO  - 10.3233/sji-190526
EP  - 613
PY  - 2019///
SN  - 1874-7655
SP  - 605
TI  - Trusted smart statistics: The challenge of extracting usable aggregate information from new data sources
T2  - Statistical Journal of the IAOS
UR  - http://dx.doi.org/10.3233/sji-190526
UR  - https://content.iospress.com/articles/statistical-journal-of-the-iaos/sji190526
UR  - http://hdl.handle.net/10044/1/75494
VL  - 35
ER  -
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