scholarly journals On the Conjunction Fallacy in Probability Judgment: New Experimental Evidence

2008 ◽  
Author(s):  
Gary Charness ◽  
Edi Karni ◽  
Dan Levin
Keyword(s):  
Experimental Evidence ◽  
Conjunction Fallacy ◽  
Probability Judgment

A violation of the monotonicity axiom: experimental evidence on the conjunction fallacy

2000 ◽  
Vol 41 (3) ◽  
pp. 263-276 ◽  
Author(s):  
Daniel John Zizzo ◽  
Stephanie Stolarz-Fantino ◽  
Julie Wen ◽  
Edmund Fantino
Keyword(s):  
Experimental Evidence ◽  
Conjunction Fallacy

scholarly journals The Bayesian Sampler: Generic Bayesian Inference Causes Incoherence in Human Probability Judgments

2018 ◽  
Author(s):  
Jian-Qiao Zhu ◽  
Adam N Sanborn ◽  
Nick Chater
Keyword(s):  
Probabilistic Models ◽  
Conjunction Fallacy ◽  
Probability Judgment ◽  
Noise Model ◽  
Probability Judgments ◽  
Probability Estimates ◽  
Bayesian Models Of Cognition ◽  
Improved Accuracy ◽  
Biases And Heuristics ◽  
The Brain

Human probability judgments are systematically biased, in apparent tension with Bayesian models of cognition. But perhaps the brain does not represent probabilities explicitly, but approximates probabilistic calculations through a process of sampling, as used in computational probabilistic models in statistics. Naïve probability estimates can be obtained by calculating the relative frequency of an event within a sample, but these estimates tend to be extreme when the sample size is small. We propose instead that people use a generic prior to improve the accuracy of their probability estimates based on samples, and we call this model the Bayesian sampler. The Bayesian sampler trades off the coherence of probabilistic judgments for improved accuracy, and provides a single framework for explaining phenomena associated with diverse biases and heuristics such as conservatism and the conjunction fallacy. The approach turns out to provide a rational reinterpretation of “noise” in an important recent model of probability judgment, the probability theory plus noise model (Costello & Watts, 2014, 2016a, 2017, 2019; Costello, Watts, & Fisher, 2018), making equivalent average predictions for simple events, conjunctions, and disjunctions. The Bayesian sampler does, however, make distinct predictions for conditional probabilities, and we show in a new experiment that this model better captures these judgments both qualitatively and quantitatively.

scholarly journals The Linda who skipped the logic classes

2021 ◽  
Author(s):  
Rivka Schlagbaum ◽  
Moshe Szweizer
Keyword(s):  
Critical Analysis ◽  
Conjunction Fallacy ◽  
Probability Judgment ◽  
Original Publication ◽  
Research Papers ◽  
Entire Field

The letter points to a logical mistake found in “The conjunction fallacy in probability judgment” published by Tversky and Kahneman. Currently, at least 5,100 research papers reference this work, and an entire field of associated studies has been created based on the paper. These works assume the correctness of the original publication and reproduce the error without due critical analysis.

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