This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
Описание
Judgment under Uncertainty: Heuristics and Biases. - PubMed - NCBI
%0 Journal Article
%1 Tversky:1974:Science:17835457
%A Tversky, A
%A Kahneman, D
%D 1974
%J Science
%K psychology
%N 4157
%P 1124-1131
%R 10.1126/science.185.4157.1124
%T Judgment under Uncertainty: Heuristics and Biases
%U https://www.ncbi.nlm.nih.gov/pubmed/17835457
%V 185
%X This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.
@article{Tversky:1974:Science:17835457,
abstract = {This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.},
added-at = {2019-10-10T21:53:30.000+0200},
author = {Tversky, A and Kahneman, D},
biburl = {https://www.bibsonomy.org/bibtex/2ff27bac83c9e0472a700949a61b136a7/jkd},
description = {Judgment under Uncertainty: Heuristics and Biases. - PubMed - NCBI},
doi = {10.1126/science.185.4157.1124},
interhash = {01155ba54ea9437ffb4ed5a243b8c9a1},
intrahash = {ff27bac83c9e0472a700949a61b136a7},
journal = {Science},
keywords = {psychology},
month = sep,
number = 4157,
pages = {1124-1131},
pmid = {17835457},
timestamp = {2019-10-10T21:53:30.000+0200},
title = {Judgment under Uncertainty: Heuristics and Biases},
url = {https://www.ncbi.nlm.nih.gov/pubmed/17835457},
volume = 185,
year = 1974
}