Applied Data Science : Data Translators Across the Disciplines
Language: English
Published by Springer, 2023
- Hardcover
- Used
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- Title
- Applied Data Science : Data Translators Across the Disciplines
- Author
- Woolford, Douglas G. (EDT); Kotsopoulos, Donna (EDT); Samuels, Boba (EDT)
- Publisher
- Springer
- Publication year
- 2023
- Condition
- As New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3031299361
- ISBN 13
- 9783031299360
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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