Statistics For Data Science And Policy Analysis
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Author | : Azizur Rahman |
Publisher | : Springer Nature |
Total Pages | : 380 |
Release | : 2020-03-31 |
Genre | : Mathematics |
ISBN | : 9811517355 |
Download Statistics for Data Science and Policy Analysis Book in PDF, Epub and Kindle
This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.
Author | : Azizur Rahman |
Publisher | : Springer |
Total Pages | : 0 |
Release | : 2021-04-01 |
Genre | : Mathematics |
ISBN | : 9789811517372 |
Download Statistics for Data Science and Policy Analysis Book in PDF, Epub and Kindle
This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.
Author | : Edward R. Tufte |
Publisher | : Prentice Hall |
Total Pages | : 204 |
Release | : 1974 |
Genre | : Political Science |
ISBN | : |
Download Data Analysis for Politics and Policy Book in PDF, Epub and Kindle
Introduction to data analysis; Predictions and projections: some issues of research design; Two-variable linear regression; Multiple regression.
Author | : Peter Bruce |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 322 |
Release | : 2017-05-10 |
Genre | : Computers |
ISBN | : 1491952911 |
Download Practical Statistics for Data Scientists Book in PDF, Epub and Kindle
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Author | : Ken Steif |
Publisher | : CRC Press |
Total Pages | : 229 |
Release | : 2021-08-18 |
Genre | : Business & Economics |
ISBN | : 100040157X |
Download Public Policy Analytics Book in PDF, Epub and Kindle
Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.
Author | : Jeffrey C. Chen |
Publisher | : Springer Nature |
Total Pages | : 365 |
Release | : 2021-09-01 |
Genre | : Mathematics |
ISBN | : 3030713520 |
Download Data Science for Public Policy Book in PDF, Epub and Kindle
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.
Author | : Gábor Békés |
Publisher | : Cambridge University Press |
Total Pages | : 741 |
Release | : 2021-05-06 |
Genre | : Business & Economics |
ISBN | : 1108483011 |
Download Data Analysis for Business, Economics, and Policy Book in PDF, Epub and Kindle
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Author | : Jose Manuel Magallanes Reyes |
Publisher | : Cambridge University Press |
Total Pages | : 317 |
Release | : 2017-09-21 |
Genre | : Computers |
ISBN | : 1107117410 |
Download Introduction to Data Science for Social and Policy Research Book in PDF, Epub and Kindle
This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
Author | : Azizur Rahman |
Publisher | : |
Total Pages | : 0 |
Release | : 2020 |
Genre | : Data mining |
ISBN | : 9789811517365 |
Download Statistics for Data Science and Policy Analysis Book in PDF, Epub and Kindle
This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.
Author | : National Research Council |
Publisher | : National Academies Press |
Total Pages | : 156 |
Release | : 2006-10-11 |
Genre | : Computers |
ISBN | : 0309102618 |
Download Improving Business Statistics Through Interagency Data Sharing Book in PDF, Epub and Kindle
U.S. business data are used broadly, providing the building blocks for key national-as well as regional and local-statistics measuring aggregate income and output, employment, investment, prices, and productivity. Beyond aggregate statistics, individual- and firm-level data are used for a wide range of microanalyses by academic researchers and by policy makers. In the United States, data collection and production efforts are conducted by a decentralized system of statistical agencies. This apparatus yields an extensive array of data that, particularly when made available in the form of microdata, provides an unparalleled resource for policy analysis and research on social issues and for the production of economic statistics. However, the decentralized nature of the statistical system also creates challenges to efficient data collection, to containment of respondent burden, and to maintaining consistency of terms and units of measurement. It is these challenges that raise to paramount importance the practice of effective data sharing among the statistical agencies. With this as the backdrop, the Bureau of Economic Analysis (BEA) asked the Committee on National Statistics of the National Academies to convene a workshop to discuss interagency business data sharing. The workshop was held October 21, 2005. This report is a summary of the discussions of that workshop. The workshop focused on the benefits of data sharing to two groups of stakeholders: the statistical agencies themselves and downstream data users. Presenters were asked to highlight untapped opportunities for productive data sharing that cannot yet be exploited because of regulatory or legislative constraints. The most prominently discussed example was that of tax data needed to reconcile the two primary business lists use by the statistical agencies.