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000005125469
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20230518152417
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230517s2021 sz a b 001c0 eng
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020
▼a 9783030713546
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035
▼a (KERIS)BIB000016590161
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040
▼a 211059
▼c 211059
▼d 211070 -
050
▼a H61.3
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090
▼a H61.3
▼b C518 -
245
▼a Data science for public policy /
▼d Jeffrey C. chen,
▼e Edward A. Rubin,
▼e Gary J. Cornwall -
260
▼a Cham :
▼b Springer,
▼c 2021 -
300
▼a 363 p. :
▼b ill. ;
▼c 26 cm -
490
▼a Springer series in the data sciences,
▼x 2365-5674 -
504
▼a Includes bibliographical references and index
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505
▼a 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
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520
▼a 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 analysts 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. -- From back cover.
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650
▼a Policy sciences
▼x Data processing -
650
▼a Data mining
-
650
▼a Political planning.
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700
▼a Chen, Jeffrey C.,
▼e author -
700
▼a Rubin, Edward A.,
▼e author -
700
▼a Cornwall, Gary J.,
▼e author -
830
▼a Springer series in the data sciences
-
830
▼a Springer series in the data sciences,
▼x 2365-5674 -
950
▼b ￡44.99
-
991
▼a 단행본
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상세정보
Data science for public policy
QR코드| 자료유형 : | 단행본 |
|---|---|
| ISBN : | 9783030713546 |
| 분류기호 : | H61.3 |
| 서명/저자사항 : | Data science for public policy / Jeffrey C. chen, Edward A. Rubin, Gary J. Cornwall |
| 발행사항 : | Cham : Springer, 2021 |
| 형태사항 : | 363 p. : ill. ; 26 cm |
| 총서사항 : | Springer series in the data sciences, 2365-5674 |
| 서지주기 : | Includes bibliographical references and index |
| 내용주기 : | 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 |
| 요약 : | 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 analysts 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. -- From back cover. |
| 일반주제명 : | Policy sciences -- Data processing -- |
| 일반주제명 : | Data mining -- |
| 일반주제명 : | Political planning. -- |
| 개인저자 : | Chen, Jeffrey C., author |
| 개인저자 : | Rubin, Edward A., author |
| 개인저자 : | Cornwall, Gary J., author |
| 언어 | 영어 |
예약
- 1. 예약현황은 홈페이지 로그인 후 예약 페이지에 확인 가능합니다.
- 2. 도착 통보된 예약자료 대출을 원하지 않는 경우에는 예약 현황에서 취소할 수 있습니다.
- 3. 기타 문의사항은 도서관에 문의 바랍니다.
무인예약대출
- 1. 무인예약대출 현황은 홈페이지 로그인 후 무인예약대출 페이지에 확인 가능합니다.
- 2. 무인예약대출자료 대출을 원하지 않는 경우에는 무인예약대출 페이지에서 신청 또는 접수상태인 경우만 취소할 수 있습니다.
- 3. 희망대출일은 신청일로부터 최대 1주일 까지 가능합니다.
- 4. 희망대출일을 선택하지 않은 경우 대출대기 통보 후 1주일까지 기기에서 대출가능합니다.
- 5. 기타 문의사항은 도서관에 문의 바랍니다.
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