Description: Data Science for Public Policy, Hardcover by Chen, Jeffrey C.; Rubin, Edward A.; Cornwall, Gary Joseph, ISBN 3030713512, ISBN-13 9783030713515, Like New Used, Free shipping in the US 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, th includes open-sourced data as well as live code, written in R and presented in not form, which readers can use and modify to practice working with data.
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Book Title: Data Science for Public Policy
Number of Pages: Xiv, 363 Pages
Language: English
Publication Name: Data Science for Public Policy
Publisher: Springer International Publishing A&G
Publication Year: 2021
Subject: Mathematical & Statistical Software, Numerical Analysis
Type: Textbook
Item Weight: 45.5 Oz
Author: Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall
Subject Area: Mathematics, Computers
Item Length: 11 in
Item Width: 8.3 in
Series: Springer Series in the Data Sciences Ser.
Format: Hardcover