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Statistik, Data Science und Big Data
[Statistics, data science, and big data]

Author

Listed:
  • Göran Kauermann

    (Ludwig-Maximilians-Universität München)

  • Helmut Küchenhoff

Abstract

Zusammenfassung In unserem Beitrag beleuchten wir die Rolle von Statistik und Data Science im Umfeld von Big Data. Data Science liegt dabei zwischen Statistik und Informatik und vereint die unterschiedlichen Konzepte der Datenanalyse. Wir zeigen anhand von zwei Beispielen auf, warum Statistik und statistisches Denken auch im Zeitalter von Big Data wichtig und hilfreich ist.

Suggested Citation

  • Göran Kauermann & Helmut Küchenhoff, 2016. "Statistik, Data Science und Big Data [Statistics, data science, and big data]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 141-150, October.
    • Handle: RePEc:spr:astaws:v:10:y:2016:i:2:d:10.1007_s11943-016-0188-y
    DOI: 10.1007/s11943-016-0188-y
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    References listed on IDEAS

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    1. William S. Cleveland, 2001. "Data Science: an Action Plan for Expanding the Technical Areas of the Field of Statistics," International Statistical Review, International Statistical Institute, vol. 69(1), pages 21-26, April.
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    Cited by:

    1. Ulrich Rendtel & Willi Seidel & Christine Müller & Florian Meinfelder & Joachim Wagner & Jürgen Chlumsky & Markus Zwick, 2022. "Statistik zwischen Data Science, Artificial Intelligence und Big Data: Beiträge aus dem Kolloquium „Make Statistics great again“ [Statistics between data science, artificial intelligence and big da," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 16(2), pages 97-147, June.

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