Fault tree analysis of software-controlled component systems based on second-order probabilities
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
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It has been observed that when people make crude estimates, they feel comfortable choosing between alternatives that differ by a half-order of magnitude (e.g., were there 100, 300, or 1000 people in the crowd?) and less comfortable making a choice on a more detailed scale, with finer granules, or on a coarser scale (like 100 or 1000). In this article, we describe two models of choosing granularity in commonsense estimates, and we show that for both models, in the optimal granularity, the next estimate is three to four times larger than the previous one. Thus, these two optimization results explain the commonsense granularity. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 843–855, 2006.