Dieckmann Nathan F, Peters Ellen, Gregory Robin
School of Nursing & Department of Public Health & Preventative Medicine, Oregon Health & Science University, Portland, OR, USA.
Decision Research, Eugene, OR, USA.
Risk Anal. 2015 Jul;35(7):1281-95. doi: 10.1111/risa.12358. Epub 2015 Mar 24.
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.
数值不确定性范围常被用于传达预测的精度。在三项研究中，我们考察了用户如何理解数值范围背后的分布情况，并检验了关于影响这些理解的显示特征的具体假设。我们讨论了这些研究得出的五个主要结论：（1）人们对数值范围背后分布的理解存在很大差异；（2）无论不确定变量是概率还是结果，分布理解似乎都相似；（3）分布理解的差异部分归因于算术能力的个体差异，算术能力较强的个体更有可能将分布理解为大致呈正态分布；（4）差异还部分归因于用于传达正确解释的常见线索的有无（例如，包含最佳估计会增加认为分布大致呈正态分布的看法）；（5）简单的图形表示可以减少分布理解中的差异。这些结果表明在气候变化及其他领域改善不确定性沟通存在重大机遇。
