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  1. Probabilistic effects in data selection.Mike Oaksford, Nick Chater & Becki Grainger - 1999 - Thinking and Reasoning 5 (3):193 – 243.
    Four experiments investigated the effects of probability manipulations on the indicative four card selection task (Wason, 1966, 1968). All looked at the effects of high and low probability antecedents (p) and consequents (q) on participants' data selections when determining the truth or falsity of a conditional rule, if p then q . Experiments 1 and 2 also manipulated believability. In Experiment 1, 128 participants performed the task using rules with varied contents pretested for probability of occurrence. Probabilistic effects were observed (...)
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  • A rational analysis of the selection task as optimal data selection.Mike Oaksford & Nick Chater - 1994 - Psychological Review 101 (4):608-631.
  • Confirmation, disconfirmation, and information in hypothesis testing.Joshua Klayman & Young-won Ha - 1987 - Psychological Review 94 (2):211-228.
  • Overcoming difficulties in Bayesian reasoning: A reply to Lewis and Keren (1999) and Mellers and McGraw (1999).Gerd Gigerenzer & Ulrich Hoffrage - 1999 - Psychological Review 106 (2):425-430.
  • How to improve Bayesian reasoning without instruction: Frequency formats.Gerd Gigerenzer & Ulrich Hoffrage - 1995 - Psychological Review 102 (4):684-704.
  • From covariation to causation: A causal power theory.Patricia W. Cheng - 1997 - Psychological Review 104 (2):367-405.
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  • Covariation in natural causal induction.Patricia W. Cheng & Laura R. Novick - 1992 - Psychological Review 99 (2):365-382.
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