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Big questions, informative data, excellent science

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  • Bowman, Adrian W.

Abstract

The expression big data is often used in a manner which implies that immediate insight is readily available. Unfortunately, this raises unrealistic expectations. A model which encapsulates the powerful concepts of statistical thinking remains an invaluable component of good analysis.

Suggested Citation

  • Bowman, Adrian W., 2018. "Big questions, informative data, excellent science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 34-36.
    • Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:34-36
    DOI: 10.1016/j.spl.2018.02.017
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    References listed on IDEAS

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    1. Pluta, Dustin & Yu, Zhaoxia & Shen, Tong & Chen, Chuansheng & Xue, Gui & Ombao, Hernando, 2018. "Statistical methods and challenges in connectome genetics," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 83-86.
    2. Dunson, David B., 2018. "Statistics in the big data era: Failures of the machine," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 4-9.
    3. Chung, Moo K., 2018. "Statistical challenges of big brain network data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 78-82.
    4. Quarteroni, Alfio, 2018. "The role of statistics in the era of big data: A computational scientist’ perspective," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 63-67.
    5. Lau, F. Din-Houn & Adams, Niall M. & Girolami, Mark A. & Butler, Liam J. & Elshafie, Mohammed Z.E.B., 2018. "The role of statistics in data-centric engineering," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 58-62.
    6. Faraway, Julian J. & Augustin, Nicole H., 2018. "When small data beats big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 142-145.
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    Keywords

    Big data; Statistical models;

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