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Data Science for Public Policy / by Jeffrey C. Chen, Edward A. Rubin, Gary J. Cornwall
(Springer Series in the Data Sciences. ISSN:23655682)
版 | 1st ed. 2021. |
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出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
出版年 | 2021 |
本文言語 | 英語 |
大きさ | XIV, 363 p. 123 illus., 111 illus. in color : online resource |
著者標目 | *Chen, Jeffrey C author Rubin, Edward A author Cornwall, Gary J author SpringerLink (Online service) |
件 名 | LCSH:Mathematics -- Data processing
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LCSH:Mathematical statistics -- Data processing 全ての件名で検索 FREE:Computational Mathematics and Numerical Analysis FREE:Statistics and Computing |
一般注記 | An Introduction -- The Case for Programming -- Elements of Programming -- Transforming Data -- Record Linkage -- Exploratory Data Analysis -- Regression Analysis -- Framing Classification -- Three Quantitative Perspectives -- Prediction -- Cluster Analysis -- Spatial Data -- Natural Language -- The Ethics of Data Science -- Developing Data Products -- Building Data Teams -- Appendix A: Planning a Data Product -- Appendix B: Interview Questions 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 HTTP:URL=https://doi.org/10.1007/978-3-030-71352-2 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783030713522 |
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電子リソース |
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EB00228065 |