Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-17T05:41:42.826Z Has data issue: false hasContentIssue false
  • English
  • Français

Implications of natural sampling in base-rate tasks

Published online by Cambridge University Press:  29 October 2007

Gernot D. Kleiter
Gernot D. Kleiter
Affiliation:
Department of Psychology, Salzburg University, A-5020 Salzburg, Austria. gernot.kleiter@sbg.ac.at
Get access Rights & Permissions [Opens in a new window]

Abstract

The hypothesis that structural properties and not frequencies per se improve base-rate sensitivity is supported from the perspective of natural sampling. Natural sampling uses a special frequency format that makes base-rates redundant. Unfortunately, however, it does not allow us to empirically investigate human understanding of essential properties of uncertainty – most importantly, the understanding of conditional probabilities in Bayes' Theorem.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 30 , Issue 3 , June 2007 , pp. 270 - 271
Copyright
Copyright © Cambridge University Press 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aitchison, J. & Dunsmore, I. R. (1975) Statistical prediction analysis. Cambridge University Press.Google Scholar
Hooper, P. M. (2007) Exact beta distributions for query probabilities in Bayesian networks. Technical Report. Department of Mathematical and Statistical Sciences, University of Alberta, Canada.Google Scholar
Kleiter, G. D. (1994) Natural sampling: Rationality without base-rates. In: Contributions to mathematical psychology, psychometrics, and methodology, ed. Fischer, G. H. & Laming, D., pp. 375–88. Springer-Verlag.Google Scholar
Kahneman, D. & Frederick, S. (1996) Propagating imprecise probabilities in Bayesian networks. Artificial Intelligence 88:143–61.Google Scholar
Kleiter, G. D. & Kardinal, M. (1995) A Bayesian approach to imprecision in belief nets. In: Symposia Gaussiana: Proceedings of the Second Gauss Symposium, Conference B: Statistical Sciences, ed. Mammitzsch, V. & Schneeweiß, H., pp. 91–105. De Gruyter.Google Scholar
Kleiter, G. D., Krebs, M., Doherty, M. E., Gavaran, H., Chadwick, R. & Brake, G. B. (1997) Do subjects understand base-rates? Organizational Behavior and Human Decision Processes 72:25–61.Google Scholar
Oaksford, M. & Chater, N. (2007) Bayesian rationality: The probabilistic approach to human reasoning. Oxford University Press.Google Scholar
Pfeifer, N. & Kleiter, G. D. (2005) Towards a mental probability logic. Psychologica Belgica 45:71–99.Google Scholar