Udvidet returret til d. 31. januar 2025

Applied Data Science - Douglas G. Woolford - Bog

Bag om Applied Data Science

The use of data to guide action is growing. Even the public uses data to guide everyday decisions! How do we develop data acumen across a broad range of fields and varying levels of expertise? How do we foster the development of effective data translators? This book explores these questions, presenting an interdisciplinary collection of edited contributions across fields such as education, health sciences, natural sciences, politics, economics, business and management studies, social sciences, and humanities. Authors illustrate how to use data within a discipline, including visualization and analysis, translating and communicating results, and pedagogical considerations. This book is of interest to scholars and anyone looking to understand the use of data science across disciplines. It is ideal in a course for non-data science majors exploring how data translation occurs in various contexts and for professionals looking to engage in roles requiring data translation.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031299360
  • Indbinding:
  • Hardback
  • Sideantal:
  • 204
  • Udgivet:
  • 11. maj 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 160x17x241 mm.
  • Vægt:
  • 477 g.
  • 8-11 hverdage.
  • 13. december 2024
På lager
Forlænget returret til d. 31. januar 2025

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  • BLACK WEEK

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Beskrivelse af Applied Data Science

The use of data to guide action is growing. Even the public uses data to guide everyday decisions! How do we develop data acumen across a broad range of fields and varying levels of expertise? How do we foster the development of effective data translators? This book explores these questions, presenting an interdisciplinary collection of edited contributions across fields such as education, health sciences, natural sciences, politics, economics, business and management studies, social sciences, and humanities. Authors illustrate how to use data within a discipline, including visualization and analysis, translating and communicating results, and pedagogical considerations. This book is of interest to scholars and anyone looking to understand the use of data science across disciplines. It is ideal in a course for non-data science majors exploring how data translation occurs in various contexts and for professionals looking to engage in roles requiring data translation.

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