Data Science for Public Policy

Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall (Autoren)

Buch | Softcover

XIV, 363 Seiten

2022 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-71354-6 (ISBN)

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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.

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

An Introduction.- The Case for Programming.- Elements of Programming.- Transforming Data.- Record Linkage.- Exploratory Data Analysis.- Regression Analysis.- Framing Classification.- Three Quantitative Perspectives.- Prediction.- Cluster Analysis.- Spatial Data.- Natural Language.- The Ethics of Data Science.- Developing Data Products.- Building Data Teams.- Appendix A: Planning a Data Product.- Appendix B: Interview Questions.

Erscheinungsdatum	03.09.2022
Reihe/Serie	Springer Series in the Data Sciences
Zusatzinfo	XIV, 363 p. 123 illus., 111 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	210 x 279 mm
Gewicht	923 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Analysis
	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Schlagworte	data sciences • Econometrics • programming • Public Policy • R • Statistics
ISBN-10	3-030-71354-7 / 3030713547
ISBN-13	978-3-030-71354-6 / 9783030713546
Zustand	Neuware