Authors:
- 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
Part of the book series: Springer Series in the Data Sciences (SSDS)
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Table of contents (16 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Bennett Institute for Public Policy, University of Cambridge, Cambridge, UK
Jeffrey C. Chen
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Department of Economics, University of Oregon, Eugene, USA
Edward A. Rubin
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Department of Commerce, Bureau of Economic Analysis, Suitland, USA
Gary J. Cornwall
About the authors
Edward A. Rubin: (1) Assistant Professor, University of Oregon (Dept. of Economics)
Gary J. Cornwall: (1) Research Economist, U.S. Bureau of Economic Analysis
Bibliographic Information
Book Title: Data Science for Public Policy
Authors: Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall
Series Title: Springer Series in the Data Sciences
DOI: https://doi.org/10.1007/978-3-030-71352-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-71351-5Published: 01 September 2021
Softcover ISBN: 978-3-030-71354-6Published: 02 September 2022
eBook ISBN: 978-3-030-71352-2Published: 01 September 2021
Series ISSN: 2365-5674
Series E-ISSN: 2365-5682
Edition Number: 1
Number of Pages: XIV, 363
Number of Illustrations: 12 b/w illustrations, 111 illustrations in colour
Topics: Computational Mathematics and Numerical Analysis, Statistics and Computing/Statistics Programs