Public Policy Analytics

• Utgivningsdatum: 2021-08-20
• Mått: 178 x 254 x undefined mm
• Vikt: 725 g
• Format: Inbunden
• Språk: Engelska
• Serie: Chapman & Hall/CRC Data Science Series
• Antal sidor: 228
• Förlag: Taylor & Francis Ltd
• ISBN: 9780367516253

• Informationsteknik: allmänt
• Politik och statsskick
• Referensverk och tvärvetenskap
• Databaser

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.

Finally, a book that connects two parallel lessons. First, how to design geospatial data science workflows in the public policy sector; and second, when applying algorithms in government, there is no free lunch. Rather than making data science in government a bleak challenge suited only the fearless, Ken sustains a tone of optimism and a sense of purpose for readers curious enough to ponder the kernels of wisdom he has sprinkled in each chapter. -- Mark Wheeler, Chief Information Officer, City of PhiladelphiaPublic Policy Analytics is a must-read for creating data-driven urban plans and policies. In crisp and compelling chapters, Dr. Steif steps through real-world problems and links them to critical methods in R. The included assignments are perfect for both self-guided students and educators. There is no better guide to data science in the public realm! -- Dr. Allison Lassiter, Assistant Professor of City & Regional Planning, Univ. of PennsylvaniaKen Steif has written a clever and instructive text to guide students of planning and public policy decision-making. This accessible book brings data science and machine learning into the realm of public policy through a series of common and compelling “use cases,” with an emphasis on the critical role of geospatial analysis. The examples provided are practical, address important social issues, and demonstrate impact. Readers will appreciate the thoughtfulness of the prose and a narration sympathetic to the challenges of doing data science in a policy environment. -- Dr. Dennis Culhane, Dana and Andrew Stone Professor of Social Policy, Univ. of Pennsylvania

0 recensioner

Inga recensioner tillgängliga.