Data Science for Public Policy
Series: Springer Series in the Data Sciences;
- Publisher's listprice EUR 53.49
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22 690 Ft (21 609 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
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22 690 Ft
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1st ed. 2021
- Publisher Springer
- Date of Publication 2 September 2022
- Number of Volumes 1 pieces, Book
- ISBN 9783030713546
- Binding Paperback
- No. of pages363 pages
- Size 279x210 mm
- Weight 934 g
- Language English
- Illustrations 12 Illustrations, black & white; 111 Illustrations, color 442
Categories
Short description:
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.
MoreLong description:
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.
Table of Contents:
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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Data Science for Public Policy
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