How do people use information presentation to make decisions in Bayesian reasoning tasks?
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 64389579
- Type
- D - Journal article
- DOI
-
10.1016/j.ijhcs.2017.11.004
- Title of journal
- International Journal of Human-Computer Studies
- Article number
- -
- First page
- 62
- Volume
- 11
- Issue
- -
- ISSN
- 1071-5819
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
A - Computer Science
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper overturns widely accepted practices in visualisation: that ""icon arrays"", common in presenting risk information (e.g. https://www.bbc.com/news/magazine-28166019) are actually disliked by those trying to interpret them; and that the ‘bias’ metric used to calculate human error in reasoning studies is, itself, biased.
Enabled funding:
- COVID-19 rapid response grant (COV0659, GBP412,700).
- PGR funding award (ESRC, NWSSDTP-9618268).
Enabled PDRAs to obtain Assistant Professorship at Chinese University of Hong Kong and Lectureship at University of Manchester .
Featured in book ‘Developing Medical Apps and mHealth Interventions’ (https://doi.org/10.1007/978-3-030-47499-7_6)."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
