Human reasoning in hypothesis-testing tasks like P. C. Wason's (1968) selection task has been depicted as prone to systematic biases. However, performance on this task has been assessed against a now outmoded falsificationist philosophy of science. Therefore, the experimental data is reassessed in the light of a Bayesian model of optimal data selection in inductive hypothesis testing. The model provides a rational analysis (J. R. Anderson, 1990) of the selection task that fits well with people's performance on both abstract and thematic versions of the task. The model suggests that reasoning in these tasks may be rational rather than subject to systematic bias
In this paper, the performance of six types of techniques for comparisons of means is examined. Thes...
Two experiments are reported that employed think-aloud methods to test predictions concerning releva...
In this paper the arguments for optimal data selection and the contrast class account of negations i...
Human reasoning in hypothesis-testing tasks like P. C. Wason's (1968) selection task has been depict...
Since it first appeared, there has been much research and critical discussion on the theory of optim...
M. Oaksford and N. Chater (O&C; 1994) presented the first quantitative model of P. C. Wason's (1966,...
A complete quantitative account of P. Wason’s (1966) abstract selection task is proposed. The accoun...
M. Oaksford and N. Chater (O&C, see record 1995-08271-001) presented the first quantitative model of...
The probabilistic approach to human reasoning is exemplified by the information gain model for the W...
Most researchers have specific expectations concerning their research questions. These may be derive...
Most researchers have specific expectations concerning their research questions. These may be derive...
K. C. Klauer (1999) argued that a Bayesian decision-theoretic rational analysis of Wason's selection...
K. C. Klauer (1999) argued that a Bayesian decision-theoretic rational analysis of Wason's selection...
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
We introduce a new model for inductive inference, by combining a Bayesian approach for representing ...
In this paper, the performance of six types of techniques for comparisons of means is examined. Thes...
Two experiments are reported that employed think-aloud methods to test predictions concerning releva...
In this paper the arguments for optimal data selection and the contrast class account of negations i...
Human reasoning in hypothesis-testing tasks like P. C. Wason's (1968) selection task has been depict...
Since it first appeared, there has been much research and critical discussion on the theory of optim...
M. Oaksford and N. Chater (O&C; 1994) presented the first quantitative model of P. C. Wason's (1966,...
A complete quantitative account of P. Wason’s (1966) abstract selection task is proposed. The accoun...
M. Oaksford and N. Chater (O&C, see record 1995-08271-001) presented the first quantitative model of...
The probabilistic approach to human reasoning is exemplified by the information gain model for the W...
Most researchers have specific expectations concerning their research questions. These may be derive...
Most researchers have specific expectations concerning their research questions. These may be derive...
K. C. Klauer (1999) argued that a Bayesian decision-theoretic rational analysis of Wason's selection...
K. C. Klauer (1999) argued that a Bayesian decision-theoretic rational analysis of Wason's selection...
Model selection is a complicated matter in science, and psychology is no exception. In particular, t...
We introduce a new model for inductive inference, by combining a Bayesian approach for representing ...
In this paper, the performance of six types of techniques for comparisons of means is examined. Thes...
Two experiments are reported that employed think-aloud methods to test predictions concerning releva...
In this paper the arguments for optimal data selection and the contrast class account of negations i...