Trustworthiness of statistical inference
Author(s)
Hand, David
Type
Journal Article
Abstract
We examine the role of trustworthiness and trust in statistical inference, arguing that it is the
extent of trustworthiness in inferential statistical tools which enables trust in the conclusions.
Certain tools, such as the p‐value and significance test, have recently come under renewed
criticism, with some arguing that they damage trust in statistics. We argue the contrary,
beginning from the position that the central role of these methods is to form the basis for
trusted conclusions in the face of uncertainty in the data, and noting that it is the misuse and
misunderstanding of these tools which damages trustworthiness and hence trust. We go on to
argue that recent calls to ban these tools would tackle the symptom, not the cause, and
themselves risk damaging the capability of science to advance, as well as risking feeding into
public suspicion of the discipline of statistics. The consequence could be aggravated mistrust of
our discipline and of science more generally. In short, the very proposals could work in quite
the contrary direction from that intended. We make some alternative proposals for tackling the
misuse and misunderstanding of these methods, and for how trust in our discipline might be
promoted.
extent of trustworthiness in inferential statistical tools which enables trust in the conclusions.
Certain tools, such as the p‐value and significance test, have recently come under renewed
criticism, with some arguing that they damage trust in statistics. We argue the contrary,
beginning from the position that the central role of these methods is to form the basis for
trusted conclusions in the face of uncertainty in the data, and noting that it is the misuse and
misunderstanding of these tools which damages trustworthiness and hence trust. We go on to
argue that recent calls to ban these tools would tackle the symptom, not the cause, and
themselves risk damaging the capability of science to advance, as well as risking feeding into
public suspicion of the discipline of statistics. The consequence could be aggravated mistrust of
our discipline and of science more generally. In short, the very proposals could work in quite
the contrary direction from that intended. We make some alternative proposals for tackling the
misuse and misunderstanding of these methods, and for how trust in our discipline might be
promoted.
Date Issued
2022-01
Date Acceptance
2021-08-31
Citation
Journal of the Royal Statistical Society Series A: Statistics in Society, 2022, 185 (1), pp.329-347
ISSN
0964-1998
Publisher
Royal Statistical Society
Start Page
329
End Page
347
Journal / Book Title
Journal of the Royal Statistical Society Series A: Statistics in Society
Volume
185
Issue
1
Copyright Statement
© 2021 The Author. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Identifier
https://rss.onlinelibrary.wiley.com/doi/10.1111/rssa.12752
Subjects
Social Sciences
Science & Technology
Physical Sciences
Social Sciences, Mathematical Methods
Statistics & Probability
Mathematical Methods In Social Sciences
Mathematics
bans
hypothesis testing
p-values
significance testing
trust
trustworthiness
TRUST
BAYES
Statistics & Probability
0104 Statistics
1403 Econometrics
1603 Demography
Publication Status
Published
Date Publish Online
2021-10-12