Data science for public policy / (Record no. 22798)
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000 -LEADER | |
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fixed length control field | 02097nam a22002297a 4500 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783030713515 |
041 ## - LANGUAGE CODE | |
Language code of text/sound track or separate title | English |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 300.285 |
Item number | CHE |
100 ## - MAIN ENTRY--AUTHOR NAME | |
Author name | Chen, Jeffrey |
245 ## - TITLE STATEMENT | |
Title | Data science for public policy / |
Statement of responsibility, etc | Jeffrey Chen ,Edward A. Rubin , Gary J. Cornwall |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Place of publication | Cham, Switzerland : |
Name of publisher | Springer, |
Year of publication | 2021. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | xiv, 363 pages : |
Other physical details | illustrations (some color), maps ; |
Dimensions | 29 cm |
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE | |
Title | Springer series in the data sciences |
505 ## - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
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 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<br/> |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Subject | Policy sciences |
General subdivision | Data processing |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Subject | Computer science |
General subdivision | Mathematics |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Subject | Statistics |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Author 2/ Editor | Rubin, Edward A. |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Author 2/ Editor | Cornwall, Gary J. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Source of classification or shelving scheme | Dewey Decimal Classification |
Koha item type | Books |
Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Use restrictions | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Bill Date | Full call number | Accession Number | Price effective from | Koha item type |
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Dewey Decimal Classification | Restricted Access | Reference | Institute of Public Enterprise, Library | Institute of Public Enterprise, Library | S Campus | 12/31/2023 | Overseas Press India | 5959.58 | 09/11/2023 | 300.285 CHE | 47882 | 12/31/2023 | Books |