虚假警告:玩弄不精确的预测

Corina Grosu, M. Grosu
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引用次数: 1

摘要

概率模型在风险评估和预防火山爆发、地震和海啸等极端事件的灾难性后果方面发挥着重要作用。概率模型在风险评估和预防火山爆发、地震和海啸等极端事件的灾难性后果方面发挥着重要作用。根据这些模型发布的预测,主要结果是对即将来临的灾难提供早期预警。然而,错误的警告也可能出现,导致不必要的恐慌和痛苦的情绪,这些都剥夺了社会的基本资源。虽然必要的科学背景是在大学期间通过概率和统计的专业课程获得的,但使用这一理论基础有一个先天的缺点。事实上,每个模型都依赖于所研究区域已经存在的类似重大事件收集的统计数据。因此,参数的估计深受特定特性的影响。这些又决定了偏差函数,该函数控制参数的估计值与实际未知值之间的差异。受到预警系统复杂性的启发,我们设计了目前的游戏,目的是增强对基于统计测试的预测的一些重要概念的理解:有偏和无偏估计以及估计参数的置信区间。在电子学习游戏中,这些概念被嵌入到一个场景中,使我们的英雄能够从最初的“海洋层面”(他得到一个秘密的海啸警报),通过“实验室层面”(他分析海洋地震),到真正的“海啸幽灵”游戏序列。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FAKE WARNING: PLAYING WITH IMPRECISE PREDICTIONS
Probabilistic models play a major role in risk assessment and prevention of disastrous consequences of extreme events such as volcano eruptions, earthquakes and tsunami. Probabilistic models play a major role in risk assessment and prevention of disastrous consequences of extreme events such as volcano eruptions, earthquakes and tsunami. The prognoses issued according to these models offer, as a principal result, early warnings concerning the approaching disaster. Nevertheless, false warnings may also appear, leading to unnecessary panic and waves of painful emotions which all deprive society of essential resources. While the necessary scientific background is acquired during the university years through specialized courses in Probability and Statistics, there is an a priori drawback to the use of this theoretical basis. In fact, each model relies on statistical data collected for similar major events already present in the region under study. The estimation of the parameters is thus deeply influenced by particular characteristics. These in turn determine the bias function which controls the difference between the estimated value of the parameter and its real unknown value. Inspired by the complexity of warning systems, we have designed our present game with the goal to enhance the understanding of some important notions which govern the prognoses based on statistical tests: biased and unbiased estimation as well as confidence interval for the estimated parameters. Included in an e-learning game, these notions are embedded into a scenario, enabling the passing of our hero from the initial “ocean level” in which he gets a secret tsunami warning, through the “lab level” in which he analyses oceanic earthquakes, to the actual “tsunami apparition” game sequence.
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