Literature DB >> 25808952

At Home on the Range? Lay Interpretations of Numerical Uncertainty Ranges.

Nathan F Dieckmann1,2, Ellen Peters3, Robin Gregory2.   

Abstract

Numerical uncertainty ranges are often used to convey the precision of a forecast. In three studies, we examined how users perceive the distribution underlying numerical ranges and test specific hypotheses about the display characteristics that affect these perceptions. We discuss five primary conclusions from these studies: (1) substantial variation exists in how people perceive the distribution underlying numerical ranges; (2) distributional perceptions appear similar whether the uncertain variable is a probability or an outcome; (3) the variation in distributional perceptions is due in part to individual differences in numeracy, with more numerate individuals more likely to perceive the distribution as roughly normal; (4) the variation is also due in part to the presence versus absence of common cues used to convey the correct interpretation (e.g., including a best estimate increases perceptions that the distribution is roughly normal); and (5) simple graphical representations can decrease the variance in distributional perceptions. These results point toward significant opportunities to improve uncertainty communication in climate change and other domains.
© 2015 Society for Risk Analysis.

Entities:  

Keywords:  Ambiguity; climate change; numeracy; risk communication; uncertainty

Year:  2015        PMID: 25808952     DOI: 10.1111/risa.12358

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  4 in total

1.  Relating Ocean Condition Forecasts to the Process of End-User Decision Making: A Case Study of the Oregon Commercial Fishing Community.

Authors:  Jessica Kuonen; Flaxen Conway; Ted Strub
Journal:  Mar Technol Soc J       Date:  2019-01-01       Impact factor: 0.708

2.  Verbal Descriptions of the Probability of Treatment Complications Lead to High Variability in Risk Perceptions: A Survey Study.

Authors:  Joshua E Rosen; Nidhi Agrawal; David R Flum; Joshua M Liao
Journal:  Ann Surg       Date:  2021-10-25       Impact factor: 13.787

3.  The Role of Type and Source of Uncertainty on the Processing of Climate Models Projections.

Authors:  Daniel M Benjamin; David V Budescu
Journal:  Front Psychol       Date:  2018-03-27

4.  The effects of communicating uncertainty on public trust in facts and numbers.

Authors:  Anne Marthe van der Bles; Sander van der Linden; Alexandra L J Freeman; David J Spiegelhalter
Journal:  Proc Natl Acad Sci U S A       Date:  2020-03-23       Impact factor: 11.205

  4 in total

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