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The Role of Statistics in the Data Revolution?

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  • Jerome H. Friedman

Abstract

The nature of data is rapidly changing. Data sets are becoming increasingly large and complex. Modern methodology for analyzing these new types of data are emerging from the fields of Data Base Managment, Artificial Intelligence, Machine Learning, Pattern Recognition, and Data Visualization. So far Statistics as a field has played a minor role. This paper explores some of the reasons for this, and why statisticians should have an interest in participating in the development of new methods for large and complex data sets.

Suggested Citation

  • Jerome H. Friedman, 2001. "The Role of Statistics in the Data Revolution?," International Statistical Review, International Statistical Institute, vol. 69(1), pages 5-10, April.
    • Handle: RePEc:bla:istatr:v:69:y:2001:i:1:p:5-10
    DOI: 10.1111/j.1751-5823.2001.tb00474.x
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    Cited by:

    1. Georg Meyer & Gediminas Adomavicius & Paul E. Johnson & Mohamed Elidrisi & William A. Rush & JoAnn M. Sperl-Hillen & Patrick J. O'Connor, 2014. "A Machine Learning Approach to Improving Dynamic Decision Making," Information Systems Research, INFORMS, vol. 25(2), pages 239-263, June.
    2. E. Marian Scott, 2023. "Framing data science, analytics and statistics around the digital earth concept," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
    3. Riccardo Boiocchi & Marco Ragazzi & Vincenzo Torretta & Elena Cristina Rada, 2023. "Critical Analysis of the GreenMetric World University Ranking System: The Issue of Comparability," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    4. Scott, E. Marian, 2018. "The role of Statistics in the era of big data: Crucial, critical and under-valued," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 20-24.
    5. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.

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