IDEAS home Printed from https://ideas.repec.org/a/aea/jecper/v10y1996i2p179-87.html
   My bibliography  Save this article

Classroom Games: Understanding Bayes' Rule

Author

Listed:
  • Charles A. Holt
  • Lisa R. Anderson

Abstract

This paper uses the technique of experimental economics to set up a classroom situation where students learn to make Bayesian decisions. The exercises allow students to discover for themselves a natural counting heuristic that corresponds to Bayes's rule and is much quicker to use in many situations. In the context of balls and urns, this heuristic involves adjusting ball counts to reflect prior probabilities. It provides a natural bridge between simple intuition and the mathematical formula for Bayes's rule that is presented in undergraduate courses in economic statistics, game theory, and managerial economics.

Suggested Citation

  • Charles A. Holt & Lisa R. Anderson, 1996. "Classroom Games: Understanding Bayes' Rule," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 179-187, Spring.
  • Handle: RePEc:aea:jecper:v:10:y:1996:i:2:p:179-87
    Note: DOI: 10.1257/jep.10.2.179
    as

    Download full text from publisher

    File URL: http://www.aeaweb.org/articles.php?doi=10.1257/jep.10.2.179
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salop, Steven C, 1987. "Evaluating Uncertain Evidence with Sir Thomas Bayes: A Note for Teachers," Journal of Economic Perspectives, American Economic Association, vol. 1(1), pages 155-159, Summer.
    2. Grether, David M., 1992. "Testing bayes rule and the representativeness heuristic: Some experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 17(1), pages 31-57, January.
    3. David M. Grether, 1980. "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 537-557.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fishman, Arthur & Fishman, Ram & Gneezy, Uri, 2019. "A tale of two food stands: Observational learning in the field," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 101-108.
    2. Debrah Meloso & Salvatore Nunnari & Marco Ottaviani, 2023. "Looking into Crystal Balls: A Laboratory Experiment on Reputational Cheap Talk," Management Science, INFORMS, vol. 69(9), pages 5112-5127, September.
    3. Gomez, Miguel I. & Rao, Vithala R. & Yuan, Hong, 2009. "A Market Experiment on Trade Promotion Budget and Allocation," Working Papers 55928, Cornell University, Department of Applied Economics and Management.
    4. Juan Pablo Herrera & Francisco Lozano Gerena, 2005. "Modelo de manadas y aprendizaje social," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 7(13), pages 133-157, July-Dece.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gergely Hajdu & Balázs Krusper, 2023. "Choice-induced Sticky Learning," Department of Economics Working Papers wuwp349, Vienna University of Economics and Business, Department of Economics.
    2. Asanov, Igor, 2021. "Bandit cascade: A test of observational learning in the bandit problem," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 150-171.
    3. Gary Charness & Edi Karni & Dan Levin, 2007. "Individual and group decision making under risk: An experimental study of Bayesian updating and violations of first-order stochastic dominance," Journal of Risk and Uncertainty, Springer, vol. 35(2), pages 129-148, October.
    4. Crosetto, Paolo & Filippin, Antonio & Katuščák, Peter & Smith, John, 2020. "Central tendency bias in belief elicitation," Journal of Economic Psychology, Elsevier, vol. 78(C).
    5. Kai Barron, 2021. "Belief updating: does the ‘good-news, bad-news’ asymmetry extend to purely financial domains?," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 31-58, March.
    6. Gary Charness & Dan Levin, 2003. "Bayesian Updating vs. Reinforcement and Affect: A Laboratory Study," Levine's Bibliography 666156000000000180, UCLA Department of Economics.
    7. Benjamin Enke & Uri Gneezy & Brian Hall & David Martin & Vadim Nelidov & Theo Offerman & Jeroen van de Ven, 2020. "Cognitive Biases: Mistakes or Missing Stakes?," CESifo Working Paper Series 8168, CESifo.
    8. Feduzi, Alberto & Runde, Jochen, 2014. "Uncovering unknown unknowns: Towards a Baconian approach to management decision-making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 124(2), pages 268-283.
    9. repec:cup:judgdm:v:3:y:2008:i::p:181-190 is not listed on IDEAS
    10. Gary Charness & Dan Levin, 2005. "When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect," American Economic Review, American Economic Association, vol. 95(4), pages 1300-1309, September.
    11. Lazarina Butkovich & Nina Butkovich & Saba Devdariani & Charles R. Plott & Han Seo, 2020. "Fake News, Information Herds, Cascades, and Economic Knowledge," Public Finance Review, , vol. 48(6), pages 806-828, November.
    12. Xiao, Wei, 2022. "Understanding probabilistic expectations – a behavioral approach," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    13. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    14. Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," NBER Working Papers 25200, National Bureau of Economic Research, Inc.
    15. Ambuehl, Sandro & Li, Shengwu, 2018. "Belief updating and the demand for information," Games and Economic Behavior, Elsevier, vol. 109(C), pages 21-39.
    16. Rabin, Matthew, 2000. "Inference by Believers in the Law of Small Numbers," Department of Economics, Working Paper Series qt4sw8n41t, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    17. repec:cup:judgdm:v:17:y:2022:i:5:p:962-987 is not listed on IDEAS
    18. Hill, Brian, 2022. "Updating confidence in beliefs," Journal of Economic Theory, Elsevier, vol. 199(C).
    19. Alexander Coutts, 2019. "Good news and bad news are still news: experimental evidence on belief updating," Experimental Economics, Springer;Economic Science Association, vol. 22(2), pages 369-395, June.
    20. Boussaidi, Ramzi & AlSaggaf, Majid Ibrahim, 2022. "Contrarian profits and representativeness heuristic in the MENA stock markets," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    21. Tsang, Ming, 2022. "Risk perception in an endogenous information environment," Research in Economics, Elsevier, vol. 76(4), pages 355-372.
    22. Alós-Ferrer, Carlos & Hügelschäfer, Sabine, 2012. "Faith in intuition and behavioral biases," Journal of Economic Behavior & Organization, Elsevier, vol. 84(1), pages 182-192.

    More about this item

    JEL classification:

    • A22 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Undergraduate
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:jecper:v:10:y:1996:i:2:p:179-87. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.