Induction as conditional probability judgment

Sergey V. Blok, Douglas L. Medin, Daniel N. Osherson

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Existing research on category-based induction has primarily focused on reasoning about blank properties, or predicates that are designed to elicit little prior knowledge. Here, we address reasoning about nonblank properties. We introduce a model of conditional probability that assumes that the conclusion prior probability is revised to the extent warranted by the evidence in the premise. The degree of revision is a function of the relevance of the premise category to the conclusion and the informativeness of the premise statement. An algebraic formulation with no free parameters accurately predicted conditional probabilities for single- and two-premise conditionals (Experiments 1 and 3), as well as problems involving negative evidence (Experiment 2).

Original languageEnglish (US)
Pages (from-to)1353-1364
Number of pages12
JournalMemory and Cognition
Volume35
Issue number6
DOIs
StatePublished - Sep 2007

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

Fingerprint Dive into the research topics of 'Induction as conditional probability judgment'. Together they form a unique fingerprint.

  • Cite this

    Blok, S. V., Medin, D. L., & Osherson, D. N. (2007). Induction as conditional probability judgment. Memory and Cognition, 35(6), 1353-1364. https://doi.org/10.3758/BF03193607