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The future of statistics and data science

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  • Olhede, Sofia C.
  • Wolfe, Patrick J.

Abstract

The ubiquity of sensing devices, the low cost of data storage, and the commoditization of computing have together led to a big data revolution. We discuss the implication of this revolution for statistics, focusing on how our discipline can best contribute to the emerging field of data science.

Suggested Citation

  • Olhede, Sofia C. & Wolfe, Patrick J., 2018. "The future of statistics and data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 46-50.
    • Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:46-50
    DOI: 10.1016/j.spl.2018.02.042
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    References listed on IDEAS

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    1. Cox, D.R. & Kartsonaki, Christiana & Keogh, Ruth H., 2018. "Big data: Some statistical issues," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 111-115.
    2. Reid, Nancy, 2018. "Statistical science in the world of big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 42-45.
    3. Dryden, Ian L. & Hodge, David J., 2018. "Journeys in big data statistics," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 121-125.
    4. Dunson, David B., 2018. "Statistics in the big data era: Failures of the machine," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 4-9.
    5. Ariel Kleiner & Ameet Talwalkar & Purnamrita Sarkar & Michael I. Jordan, 2014. "A scalable bootstrap for massive data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(4), pages 795-816, September.
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    Cited by:

    1. Hassani, Hossein & Beneki, Christina & Silva, Emmanuel Sirimal & Vandeput, Nicolas & Madsen, Dag Øivind, 2021. "The science of statistics versus data science: What is the future?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).

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