Data Science for Public Policy (Record no. 39197)

000 -LEADER
fixed length control field 01295nam a22001337a 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783030713546
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Chen, Jeffrey C.
245 ## - TITLE STATEMENT
Title Data Science for Public Policy
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Switzerland :
Name of publisher Springer Nature,
Year of publication 2021
520 ## - SUMMARY, ETC.
Summary, etc 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.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Edward A. Rubin
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Gary J. Cornwall
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Permanent Location Current Location Date acquired Source of acquisition Cost, normal purchase price Accession Number Cost, replacement price Price effective from Koha item type
        NASSDOC Library NASSDOC Library 2024-05-20 7 2956.58 54333 4548.59 2024-05-20 Books