Data Science For Public Policy
Data Science For Public Policy
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Author
Author
Edward A. Rubin, Gary J. Cornwell, Jeffrey K. Chen / Эдвард А. Рубин, Гэри Дж. Корнуэлл, Джеффри К. Чен
Dimension
Dimension
210x279mm (8,3'x11')
ISBN
ISBN
9783030713515
Format
Format
Hardcover
Language
Language
English
Page Count
Page Count
363
Publisher
Publisher
Springer
Year of book publication
Year of book publication
2021
Data Science For Public Policy
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.
SPECIFICATIONS:
Author:Edward A. Rubin, Gary J. Cornwell, Jeffrey K. Chen - Эдвард А. Рубин, Гэри Дж. Корнуэлл, Джеффри К. Чен
Publisher:Springer
Language:English
Publication Date:2021
Number of pages:363 pst
Format:Hardcover
Width:210 mm / 8,3'
Height:279 mm / 11'
Weight:1289 g
ISBN:9783030713515