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Applied data sciencedata translators across the disciplines /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applied data scienceedited by Douglas G. Woolford, Donna Kotsopoulos, Boba Samuels.
Reminder of title:	data translators across the disciplines /
other author:	Woolford, Douglas G.
Published:	Cham :Springer International Publishing :2023.
Description:	1 online resource (xii, 190 p.) :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Big data.
Online resource:	https://doi.org/10.1007/978-3-031-29937-7
ISBN:	9783031299377$q(electronic bk.)

Applied data sciencedata translators across the disciplines /
Applied data sciencedata translators across the disciplines /[electronic resource] :edited by Douglas G. Woolford, Donna Kotsopoulos, Boba Samuels. - Cham :Springer International Publishing :2023. - 1 online resource (xii, 190 p.) :ill., digital ;24 cm. - Studies in big data,v. 1252197-6511 ;. - Studies in big data ;v.1..

Translating science into actionable policy information - a perspective on the IPCC process -- Data in Observational Astronomy -- On Becoming a Data-Scientist, Beyond Translation: Discovering Best Practices for Evidence-Informed Decision Making for Public Health Practices -- Concern for self-health during the COVID-19 pandemic in Canada: How to use quantitative data to tell an intersectional story?- Community-based participatory research and respondent-driven sampling: A statistician's, community partner's and students' perspectives on a successful partnership.

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.

ISBN: 9783031299377$q(electronic bk.)

Standard No.: 10.1007/978-3-031-29937-7doiSubjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Applied data sciencedata translators across the disciplines /
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