Hertwig,R.
Hoffrage,U.
Sparr,R.

Much of the world is in a state of predictable imbalance. The goal of this chapter is to analyze how valuable the assumption of systematic environment imbalance is for performing rough estimates. By such estimates, we mean the routine assessment of quantities (e.g., frequencies, sizes, amounts) in which people regularly engage when they infer the quantitative value of an object (such as its frequency, size, value, or quality). To this end, we first outline how systematic environment imbalance can be described using the framework of power laws. Then, we investigate to what extent power-law characteristics as well as other statistical properties of real-world environments can be allies of simple heuristics in performing rough-and-ready estimates, thereby leading to ecological rationality. For this purpose we will introduce two heuristics: The first, QuickEst, uses simple building blocks for ordered cue search and stopping and is particularly suited for skewed environments. The second, the mapping model or mapping heuristic, is built on the simplifying decision mechanism of tallying and can be applied to a broader range of distributions. (PsycINFO Database Record (c) 2012 APA, all rights reserved). (create)

Hertwig, R., Hoffrage, U., & Sparr, R. (2012). How estimation can benefit from an imbalanced world. In P. M. Todd, G. Gigerenzer & the ABC Research Group, Ecological rationality: Intelligence in the world (pp. 379-406). New York: Oxford University Press.

Publication year	2012
Document type:	In book
Publication status:	Published
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Keywords:	decision makingecologyenvironmentestimationheuristic modelingheuristicsrationalitydecisionsecological rationalityestimationheuristicssystematic environment imbalance