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Failures of explaining away and screening off in described versus experienced causal learning scenarios
by
Waldmann, Michael R.
, Rehder, Bob
in
Adult
/ Bayes Theorem
/ Behavioral Science and Psychology
/ Bias
/ Causal models
/ Causality
/ Cognition & reasoning
/ Cognitive Psychology
/ Humans
/ Learning
/ Learning - physiology
/ Markov Chains
/ Norms
/ Principles
/ Property
/ Psychology
/ Reasoning
/ Studies
/ Thinking - physiology
/ Variables
/ Viruses
/ Young Adult
2017
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Failures of explaining away and screening off in described versus experienced causal learning scenarios
by
Waldmann, Michael R.
, Rehder, Bob
in
Adult
/ Bayes Theorem
/ Behavioral Science and Psychology
/ Bias
/ Causal models
/ Causality
/ Cognition & reasoning
/ Cognitive Psychology
/ Humans
/ Learning
/ Learning - physiology
/ Markov Chains
/ Norms
/ Principles
/ Property
/ Psychology
/ Reasoning
/ Studies
/ Thinking - physiology
/ Variables
/ Viruses
/ Young Adult
2017
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Do you wish to request the book?
Failures of explaining away and screening off in described versus experienced causal learning scenarios
by
Waldmann, Michael R.
, Rehder, Bob
in
Adult
/ Bayes Theorem
/ Behavioral Science and Psychology
/ Bias
/ Causal models
/ Causality
/ Cognition & reasoning
/ Cognitive Psychology
/ Humans
/ Learning
/ Learning - physiology
/ Markov Chains
/ Norms
/ Principles
/ Property
/ Psychology
/ Reasoning
/ Studies
/ Thinking - physiology
/ Variables
/ Viruses
/ Young Adult
2017
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Failures of explaining away and screening off in described versus experienced causal learning scenarios
Journal Article
Failures of explaining away and screening off in described versus experienced causal learning scenarios
2017
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Overview
Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of
explaining away
and
screening off,
subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the
rich-get-richer
principle. This research focuses on these two failures comparing tasks in which causal scenarios are merely described (via verbal statements of the causal relations) versus experienced (via samples of data that manifest the intervariable correlations implied by the causal relations). Our key finding is that we obtained stronger deviations from normative predictions in the described conditions that highlight the instructed causal model compared to those that presented data. This counterintuitive finding indicate that a theory of causal reasoning and learning needs to integrate normative principles with biases people hold about causal relations.
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