IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v75y2007i3p397-405.html
   My bibliography  Save this article

Foundational Value of Statistics Education for Management Curriculum

Author

Listed:
  • Hirokuni Tamura

Abstract

The purpose of this paper is to propose a unique and distinct value of statistics education for management. The 1986 inaugural conference on Making Statistics More Effective in Schools of Business (MSMESB) proposed valuable guidelines for reforming statistics education in schools of business. However, a survey conducted by McAlevey & Everett (2001) identified that their impact has been minimal, and argued that structural problems many business schools have are the potential cause. We argue these structural problems exist because the value of the body of statistical tools for management is ambiguous and has not been made explicit. The unique and distinct value of statistics for management can be identified as the body of tools necessary to meet the inherent needs of a manager charged with making predictive judgments facing data. The need arises because human information‐processing capacity is quite limited, as the findings of researchers in cognitive psychology testify. These findings also affirm that the basic statistical concepts needed for processing data cannot be learned from management experiences. The model of a manager faced with data, while considering the evidence of inherent limitations of human information‐processing capacity, establishes the foundational value of statistics training in the management curriculum. Statistics education in business schools will be made more effective when management educators recognize such value of the discipline, lend their support and reward the ownership commitment for continuous improvement and innovations of the business statistics curriculum. Le but de cet article est de proposer une valeur unique et particulière de l'enseignement des statistiques dans le domaine de la gestion. La conférence inaugurale de 1986 traitant des moyens d'améliorer l'efficacité de cet enseignement dans les écoles de gestion a proposé des lignes directrices valables pour la réforme de l'enseignement des statistiques dans les écoles de gestion. Néanmoins, un sondage effectué par McAlevey & Everett (2001), a identifié leur impact comme étant minimal et en attribue la cause probable aux problèmes structurels des écoles de gestion. Nous considérons que ces problèmes existent parce que la valeur du corpus statistique de gestion est ambigüe et n'a pas été mise en lumière. La valeur unique et distincte des statistiques de gestion peut être identifiée comme un corpus d'outils nécessaires pour répondre aux besoins inhérents d'un gestionnaire chargé de faire des prévisions au moyen d'informations brutes. Ce besoin vient du fait que la capacité humaine de traitement de l'information est limitée ainsi qu'en témoignent les recherches en psychologie cognitive. Ces résultats affirment également que les concepts statistiques basiques nécessaires pour le traitement de l'information ne peuvent être acquis par l'expérience de la gestion. Le modèle du gestionnaire confronté de l'information, une fois l'évidence des limites des capacités humaines en matière de traitement de l'information est prise en compte, établi la valeur fondatrice de l'entrainement aux statistiques dans un curriculum de gestion. L'enseignement des statistiques dans les écoles de commerce sera plus efficace quand les responsables de l'éducation reconnaitront cette valeur de la discipline, y apporteront leur soutien et récompenseront les actions visant à l'amélioration et l'innovation constante au sein du curriculum statistique de gestion.

Suggested Citation

  • Hirokuni Tamura, 2007. "Foundational Value of Statistics Education for Management Curriculum," International Statistical Review, International Statistical Institute, vol. 75(3), pages 397-405, December.
  • Handle: RePEc:bla:istatr:v:75:y:2007:i:3:p:397-405
    DOI: 10.1111/j.1751-5823.2007.00032.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1751-5823.2007.00032.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1751-5823.2007.00032.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080.
    2. Easton, George & Roberts, Harry V & Tiao, George C, 1988. "Making Statistics More Effective in Schools of Business," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 247-260, April.
    3. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    4. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    5. Sandra E. Strasser & Ceyhun Ozgur, 1995. "Undergraduate Business Statistics: A Survey of Topics and Teaching Methods," Interfaces, INFORMS, vol. 25(3), pages 95-103, June.
    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. Prof. Kamal Kishore Jain & Kumar Kunal Kamal, 2010. "Reassessing the Curriculum-Competency Alignment in MBA Programs," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 1(1), pages 68-75, December.

    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. Maria Heracleous & Andreas Koutris & Aris Spanos, 2006. "Testing for Structural Breaks and other forms of Non-stationarity: a Misspecification Perspective," Computing in Economics and Finance 2006 493, Society for Computational Economics.
    2. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    3. Entorf, Horst, 1997. "Random walks with drifts: Nonsense regression and spurious fixed-effect estimation," Journal of Econometrics, Elsevier, vol. 80(2), pages 287-296, October.
    4. Beaulieu, Anne & Patry, Michel & Raynauld, Jacques, 1989. "L’analyse de la productivité des transporteurs aériens canadiens dans les années soixante-dix : pour un autre plan de vol," L'Actualité Economique, Société Canadienne de Science Economique, vol. 65(2), pages 183-207, juin.
    5. Nasr, G. E. & Badr, E. A. & Dibeh, G., 2000. "Econometric modeling of electricity consumption in post-war Lebanon," Energy Economics, Elsevier, vol. 22(6), pages 627-640, December.
    6. Mongkolporn, Veerasak & Yin, Xiangkang, 2005. "How does the entry of new firms change demand? An empirical estimation for a Thai telecommunications company," Journal of Asian Economics, Elsevier, vol. 16(4), pages 688-703, August.
    7. PHILIP E.T. LEWIS & GARRY A. MacDONALD, 1993. "Testing for Equilibrium in the Australian Wage Equation," The Economic Record, The Economic Society of Australia, vol. 69(3), pages 295-304, September.
    8. Huang, Bwo-Nung & Hwang, M.J. & Yang, C.W., 2008. "Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach," Ecological Economics, Elsevier, vol. 67(1), pages 41-54, August.
    9. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    10. de Meulemeester, Jean-Luc & Rochat, Denis, 1995. "A causality analysis of the link between higher education and economic development," Economics of Education Review, Elsevier, vol. 14(4), pages 351-361, December.
    11. David Alan Aschauer, 1990. "Is Government Spending Stimulative?," Contemporary Economic Policy, Western Economic Association International, vol. 8(4), pages 30-46, October.
    12. Tang, Chor Foon, 2011. "Tourism, real output and real effective exchange rate in Malaysia: a view from rolling sub-samples," MPRA Paper 29379, University Library of Munich, Germany.
    13. Thomas R. Harris & J. Scott Shonkwiler & George E. Ebai, 1999. "Dynamic Nonmetropolitan Export-Base Modeling," The Review of Regional Studies, Southern Regional Science Association, vol. 29(2), pages 115-138, Fall.
    14. Mur, Jesus, 2002. "On the specification of spatial econometric models," ERSA conference papers ersa02p012, European Regional Science Association.
    15. Rybinski, Krzysztof, 1997. "Testing Integration of Macroeconomic Time Series in Transitional Socialist Economies. A Modification of Perron Test," Economic Change and Restructuring, Springer, vol. 30(2-3), pages 127-179.
    16. Tung Liu & Lee C. Spector, 2005. "Dynamic employment adjustments over business cycles," Empirical Economics, Springer, vol. 30(1), pages 151-169, January.
    17. Nasir, Muhammad Ali & Morgan, Jamie, 2023. "Paradox of stationarity? A policy target dilemma for policymakers," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 142-145.
    18. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    19. Ogunleye, Eric Kehinde, 2008. "Natural resource abundance in Nigeria: From dependence to development," Resources Policy, Elsevier, vol. 33(3), pages 168-174, September.
    20. Elbadawi, Ibrahim A. & Schmidt-Hebbel, Klaus, 1991. "Macroeconomic structure and policy in Zimbabwe, analysis and empirical model : 1965-1988," Policy Research Working Paper Series 771, The World Bank.

    More about this item

    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:bla:istatr:v:75:y:2007:i:3:p:397-405. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/isiiinl.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.