When people evaluate explanations in uncertain situations, the latent scope bias occurs. It refers to the tendency to perceive explanations that do not include unobservable events as plausible. Previous studies have proposed the inferred evidence account, which states that the bias is caused by underestimating the occurrence probability of unobservable events. Additionally, this account assumes that humans use Bayesian probability reasoning in evaluating such explanations. However, previous studies on this bias have not examined the Bayesian probabilistic reasoning component. This study measured subjective probabilities of explanations and modeled the reasoning process. As a result, it was found that latent scope bias is caused by Bayesian ...
On theoretical grounds Bayesian probability theory is arguably the sound-est approach to uncertain r...
The rationality of human causal judgments has been the focus of a great deal of recent research. We ...
The human capacity for causal judgment has long been thought to depend on an ability to consider cou...
This PhD is concerned with the causal Bayesian framework account of probabilistic judgement (Krynski...
Ambiguous observations result in imprecise estimations of subjective probabilities for rule-based ca...
Recent research comparing mental models theory and causal Bayes nets for their ability to account fo...
gmail.com Causal inference is a fundamental component of cognition and perception. Probabilistic the...
We suggest a normative model for the evaluation of explanations B because A based on probabilistic c...
A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelate...
Four experiments examined the locus of impact of causal knowledge on consideration of alternative hy...
People often makes inductive inferences that go beyond the data that are given. In order to generate...
People often struggle when making Bayesian probabilistic estimates on the basis of competing sources...
In this article, I will show how several observed biases in human probabilistic reasoning can be par...
Ambiguous causal evidence in which the covariance of the cause and effect is partially known is perv...
Bayesian theories of cognition assume that people can integrate probabilities rationally. However, s...
On theoretical grounds Bayesian probability theory is arguably the sound-est approach to uncertain r...
The rationality of human causal judgments has been the focus of a great deal of recent research. We ...
The human capacity for causal judgment has long been thought to depend on an ability to consider cou...
This PhD is concerned with the causal Bayesian framework account of probabilistic judgement (Krynski...
Ambiguous observations result in imprecise estimations of subjective probabilities for rule-based ca...
Recent research comparing mental models theory and causal Bayes nets for their ability to account fo...
gmail.com Causal inference is a fundamental component of cognition and perception. Probabilistic the...
We suggest a normative model for the evaluation of explanations B because A based on probabilistic c...
A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelate...
Four experiments examined the locus of impact of causal knowledge on consideration of alternative hy...
People often makes inductive inferences that go beyond the data that are given. In order to generate...
People often struggle when making Bayesian probabilistic estimates on the basis of competing sources...
In this article, I will show how several observed biases in human probabilistic reasoning can be par...
Ambiguous causal evidence in which the covariance of the cause and effect is partially known is perv...
Bayesian theories of cognition assume that people can integrate probabilities rationally. However, s...
On theoretical grounds Bayesian probability theory is arguably the sound-est approach to uncertain r...
The rationality of human causal judgments has been the focus of a great deal of recent research. We ...
The human capacity for causal judgment has long been thought to depend on an ability to consider cou...