Category coherence in children's inductive inferences with cross-classified entities

Pre-history of Probability

10.1093/oxfordhb/9780199607617.013.3 ◽

2017 ◽

Author(s):

James Franklin

Keyword(s):

Legal Theory ◽

Moral Theology ◽

Difficult Problem ◽

Reasonable Doubt ◽

Games Of Chance ◽

Uncertain Evidence ◽

Price Of Risk ◽

History Of ◽

Inductive Inferences ◽

Theory Of Evidence

The history of the evaluation of uncertain evidence before the quantification of probability in 1654 is a mass of examples relevant to current debates. They deal with matters that in general are as unquantified now as ever – the degree to which evidence supports theory, the strength and justification of inductive inferences, the weight of testimony, the combination of pieces of uncertain evidence, the price of risk, the philosophical nature of chance, and the problem of acting in case of doubt. Concepts similar to modern “proof beyond reasonable doubt” were developed especially in the legal theory of evidence. Moral theology discussed “probabilism”, the doctrine that one could follow a probable opinion in ethics even if the opposite was more probable. Philosophers understood the difficult problem of induction. Legal discussion of “aleatory contracts” such as insurance and games of chance developed the framework in which the quantification of probability eventually took place.

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Preschool Children's Use of Trait Labels to Make Inductive Inferences

Journal of Experimental Child Psychology ◽

10.1006/jecp.1999.2555 ◽

2000 ◽

Vol 77 (1) ◽

pp. 1-19 ◽

Cited By ~ 84

Author(s):

Gail D. Heyman ◽

Susan A. Gelman

Keyword(s):

Inductive Inferences

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Inferring Causal Relations by Analogy

10.1093/oxfordhb/9780199399550.013.25 ◽

2017 ◽

Author(s):

Keith J. Holyoak ◽

Hee Seung Lee

Keyword(s):

Analogical Reasoning ◽

Causal Model ◽

Causal Knowledge ◽

Common Pattern ◽

Causal Relations ◽

Analogical Inference ◽

Psychological Evidence ◽

Inductive Inferences ◽

Novel Target ◽

Constituent Elements

When two situations share a common pattern of relationships among their constituent elements, people often draw an analogy between a familiar source analog and a novel target analog. This chapter reviews major subprocesses of analogical reasoning and discusses how analogical inference is guided by causal relations. Psychological evidence suggests that analogical inference often involves constructing and then running a causal model. It also provides some examples of analogies and models that have been used as tools in science education to foster understanding of critical causal relations. A Bayesian theory of causal inference by analogy illuminates how causal knowledge, represented as causal models, can be integrated with analogical reasoning to yield inductive inferences.

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