Public Policy Analytics : Code and Context for Data Science in Government

Ken Steif

ISBN 10: 0367507617 / ISBN 13: 9780367507619

Published by CRC Press, 2021

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand 'spatial process' and develop spatial analytics; how to develop 'useful' predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and 'Planning' are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.

Seller Inventory # 9780367507619

Bibliographic Details

• Title: Public Policy Analytics : Code and Context for Data Science in Government
• Publisher: CRC Press
• Publication Date: 2021
• Language: English
• ISBN 10: 0367507617
• ISBN 13: 9780367507619
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 254W x 178H x 13D millimeters 254 millimeters width by 178 millimeters height by 13 millimeters depth
• Weight: 442 grams

About this title

Synopsis

Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.

About the Author

Ken Steif Ph.D is the Director of the Master of Urban Spatial Analytics program at the University of Pennsylvania and an Associate Professor of Practice in the City Planning Program. He teaches courses on the application of spatial analysis, statistics, predictive modeling and data visualization to solve traditional and contemporary public policy programs. Dr. Steif also is the founder of a consultancy that develops analytics for both public and private-sector clients. He lives in West Philadelphia with his wife Diana and sons Emil and Malcolm. You can follow him on Twitter @KenSteif.