Applied Data Science

Douglas G. Woolford

ISBN 10: 3031299361 / ISBN 13: 9783031299360

Published by Springer, Springer Mai 2023, 2023

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 204 pp. Englisch.

Seller Inventory # 9783031299360

Bibliographic Details

• Title: Applied Data Science
• Publisher: Springer, Springer Mai 2023
• Publication Date: 2023
• Language: English
• ISBN 10: 3031299361
• ISBN 13: 9783031299360
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 17D millimeters 241 millimeters width by 160 millimeters height by 17 millimeters depth
• Weight: 477 grams

About this title

Synopsis

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.