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Springer Series in the Data Sciences
cover

Data Science for Public Policy

Authors: Chen, Jeffrey, Rubin, Edward, Cornwall, Gary Joseph

  • Combines anecdotes from public sector experience with technical aspects of field
  • Addresses current topics in ethics and fairness, data product development, and team organization in data science
  • Includes data sets and functioning code examples
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eBook $59.99
price for Mexico
  • The eBook version of this title will be available soon
  • Due: 24 de septiembre de 2021
  • ISBN 978-3-030-71352-2
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover $79.99
price for Mexico
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: 27 de agosto de 2021
  • ISBN 978-3-030-71351-5
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
About this Textbook

This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, this book emphasizes the process of asking relevant questions to inform public policy. Its techniques and approaches emphasize data-driven practices, beginning with the basic programming paradigms that occupy the majority of an analyst’s time and advancing to the practical applications of statistical learning and machine learning. The text considers two divergent, competing perspectives to support its applications, incorporating techniques from both causal inference and prediction. Additionally, the book includes open-sourced data as well as live code, written in R and presented in notebook form, which readers can use and modify to practice working with data.

About the authors

Jeffrey C. Chen: (1) Affiliated Researcher, Bennett Institute for Public Policy, University of Cambridge
Edward A. Rubin: (1) Assistant Professor, University of Oregon (Dept. of Economics)
Gary J. Cornwall: (1) Research Economist, U.S. Bureau of Economic Analysis

Buy this book

eBook $59.99
price for Mexico
  • The eBook version of this title will be available soon
  • Due: 24 de septiembre de 2021
  • ISBN 978-3-030-71352-2
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover $79.99
price for Mexico
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: 27 de agosto de 2021
  • ISBN 978-3-030-71351-5
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
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Bibliographic Information

Bibliographic Information
Book Title
Data Science for Public Policy
Authors
Series Title
Springer Series in the Data Sciences
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-71352-2
DOI
10.1007/978-3-030-71352-2
Hardcover ISBN
978-3-030-71351-5
Series ISSN
2365-5674
Edition Number
1
Number of Pages
XIV, 365
Number of Illustrations
12 b/w illustrations, 111 illustrations in colour
Topics