Skip to main content Accessibility help
×
Hostname: page-component-77c89778f8-rkxrd Total loading time: 0 Render date: 2024-07-20T13:20:43.374Z Has data issue: false hasContentIssue false

5 - Less Is More in Covariation Detection – Or Is It?

Published online by Cambridge University Press:  02 February 2010

Peter Juslin
Affiliation:
University of Uppsala, Sweden
Klaus Fiedler
Affiliation:
University of Heidelberg, Germany
Nick Chater
Affiliation:
University Collage, London
Klaus Fiedler
Affiliation:
Ruprecht-Karls-Universität Heidelberg, Germany
Peter Juslin
Affiliation:
Umeå Universitet, Sweden
Get access

Summary

INTRODUCTION

One of the more celebrated conclusions in cognitive psychology refers to the limited computational capacity of controlled thought, as typically epitomized by Miller's (1956) estimate of a short-term-memory holding capacity of “seven-plus-or-minus-two” chunks. That people can only keep a limited amount of information active for controlled processing at any moment in time has inspired humbling conclusions in regard to problem solving (Newell & Simon, 1972), reasoning (Evans, Newstead, & Byrne, 1993), and, perhaps especially, judgment and decision making (Gilovich, Griffin, & Kahneman, 2002). This limitation is often raised as a main obstacle to people's attainment of classical rationality, suggesting that at best people can aspire to bounded rationality (Simon, 1990). In the context of this volume the implication is that at any moment in time controlled processes of thought can only access a small sample of observations.

The default interpretation seems to be to emphasize the liabilities of these limitations and to regard the current state in the evolutionary development as representing at best a local maximum. Organisms are thus restricted to limited samples of information, although there is agreement that on normative grounds as much information as possible is needed to optimize judgments and decisions. More rarely is the question raised of whether there can be a functional significance attached to apparent cognitive limitations.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2005

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

Anderson, R. B., Doherty, M. E., Berg, N. D., & Friedrich, J. C. (2005). Sample size and the detection of correlation – A signal-detection account: A comment on Kareev (2000) and Juslin and Olsson (2005). Psychological Review, 112, 268–279CrossRefGoogle Scholar
Berger, J. O. (1985). Statistical decision theory and Bayesian analysis. New York: Springer-VerlagCrossRefGoogle Scholar
Broadbent, D. E. (1975). The magic number seven after fifteen years. In Kennedy, A. & Wilkes, A. (Eds.), Studies in long term memory, (pp. 3–18). London: WileyGoogle Scholar
Chater, N., Crocker, M., & Pickering, M. (1998). The rational analysis of inquiry: The case of parsing. In: Chater, N. & Oaksford, M. (Eds), Rational models of cognition (pp. 441–468). Oxford: Oxford University PressGoogle Scholar
Corter, J., & Gluck, M. (1992). Explaining basic categories: Feature predictability and information. Psychological Bulletin, 111, 291–303CrossRefGoogle Scholar
Elman, J. L. (1993). Learning and development in neural networks: the importance of starting small. Cognition, 48, 71–99CrossRefGoogle ScholarPubMed
Evans, J., Newstead, S., & Byrne, R. (1993). Human reasoning: The psychology of deduction. Potomac, Maryland: Lawrence Erlbaum AssociatesGoogle Scholar
Fiedler, K., & Kareev, Y. (2004). Does decision quality (always) increase with the size of information samples? Some vicissitudes in applying the Law of Large Numbers. Manuscript submitted for publication. Discussion Paper #347, Center for the Study of Rationality, The Hebrew University, JerusalemGoogle Scholar
Gilovich, T., Griffin, D., & Kahneman, D. (2002). Heuristics and biases: The psychology of intuitive judgment. Cambridge: Cambridge University PressCrossRefGoogle Scholar
Good, I. J. (1950). Probability and the weighing of evidence. London: Charles GriffinGoogle Scholar
Humphreys, G. W., & Heinke, D. (1998). Spatial representation and selection in the brain: Neuropsychological and computational constraints. Visual Cognition, 5, 9–47Google Scholar
Juslin, P., & Olsson, H. (2005). Capacity limitations and the detection of correlations: Comment on Kareev (2000). Psychological Review, 112, 256–267CrossRefGoogle Scholar
Kareev, Y. (1995). Through a narrow window: working memory capacity and the detection of correlation. Cognition, 56, 263–269CrossRefGoogle Scholar
Kareev, Y. (2000). Seven (indeed, plus or minus two) and the detection of correlation. Psychological Review, 107, 397–402CrossRefGoogle Scholar
Kareev, Y., Lieberman, I., & Lev, M. (1997). Through a narrow window: Sample size and the perception of correlation. Journal of Experimental Psychology: General, 126, 278–287CrossRefGoogle Scholar
Lindley, D. V. (1956). On a measure of the information provided by an experiment. Annals of Mathematical Statistics, 27, 986–1005CrossRefGoogle Scholar
MacGregor, J. N. (1987). Short term memory capacity: Limitation or optimization?Psychological Review, 94, 107–108CrossRefGoogle Scholar
MacKay, D. J. C. (1992). Information-based objective functions for active data selection. Neural Computation, 4, 590–604CrossRefGoogle Scholar
MacMillan, N. A., & Creelman, C. D. (1991). Detection theory: A user's guide. New York: Cambridge University PressGoogle Scholar
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81–97CrossRefGoogle ScholarPubMed
Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-HallGoogle Scholar
Oaksford, M., & Chater, N. (1994). A rational analysis of the selection task as optimal data selection. Psychological Review, 101, 608–631CrossRefGoogle Scholar
Simon, H. A. (1990). Invariants of human behavior. Annual Review of Psychology, 41, 1–19CrossRefGoogle ScholarPubMed
Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27, 379–423, 623–656CrossRefGoogle Scholar
Thuijsman, F., Peleg, B.Amitai, M., & Shmida, A. (1995). Automata, matching and foraging behavior of bees. Journal of Theoretical Biology, 175, 305–316CrossRefGoogle Scholar
Turkewitz, G., & Kenny, P. A. (1982). Limitations on input as a basis for neural organization and perceptual development: A preliminary theoretical statement. Developmental Psychobiology, 15, 357–368CrossRefGoogle ScholarPubMed
Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton, NJ: Princeton University PressGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×