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Foundational Value of Statistics Education for Management Curriculum

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  • 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
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    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.
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    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.

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