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Statistics For Data Science And Policy Analysis
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Book Synopsis Statistics for Data Science and Policy Analysis by : Azizur Rahman
Download or read book Statistics for Data Science and Policy Analysis written by Azizur Rahman and published by Springer. This book was released on 2021-04-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistics for Data Science and Policy Analysis by : Azizur Rahman
Download or read book Statistics for Data Science and Policy Analysis written by Azizur Rahman and published by Springer Nature. This book was released on 2020-03-31 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce
Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Introduction to Data Science for Social and Policy Research by : Jose Manuel Magallanes Reyes
Download or read book Introduction to Data Science for Social and Policy Research written by Jose Manuel Magallanes Reyes and published by Cambridge University Press. This book was released on 2017-09-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.
Book Synopsis Data Analysis for Business, Economics, and Policy by : Gábor Békés
Download or read book Data Analysis for Business, Economics, and Policy written by Gábor Békés and published by Cambridge University Press. This book was released on 2021-05-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Book Synopsis Public Policy Analytics by : Ken Steif
Download or read book Public Policy Analytics written by Ken Steif and published by CRC Press. This book was released on 2021-08-18 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistics for Data Science and Policy Analysis by : Azizur Rahman
Download or read book Statistics for Data Science and Policy Analysis written by Azizur Rahman and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Science for Public Policy by : Jeffrey C. Chen
Download or read book Data Science for Public Policy written by Jeffrey C. Chen and published by Springer Nature. This book was released on 2021-09-01 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Analysis for Politics and Policy by : Edward R. Tufte
Download or read book Data Analysis for Politics and Policy written by Edward R. Tufte and published by Prentice Hall. This book was released on 1974 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to data analysis; Predictions and projections: some issues of research design; Two-variable linear regression; Multiple regression.
Book Synopsis Data Analysis for Social Science by : Elena Llaudet
Download or read book Data Analysis for Social Science written by Elena Llaudet and published by Princeton University Press. This book was released on 2022-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--
Book Synopsis Statistics for Data Scientists by : Maurits Kaptein
Download or read book Statistics for Data Scientists written by Maurits Kaptein and published by Springer Nature. This book was released on 2022-02-02 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treatment of probability and statistical principles. Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, etc.), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science.
Book Synopsis Understanding Political Science Statistics by : Peter Galderisi
Download or read book Understanding Political Science Statistics written by Peter Galderisi and published by Routledge. This book was released on 2015-03-12 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: In politics, you begin by asking theoretically interesting questions. Sometimes statistics can help answer those questions. When it comes to applied statistics, students shouldn’t just learn a vast array of formula—they need to learn the basic concepts of statistics as solutions to particular problems. Peter Galderisi demonstrates that statistics are a summary of how to answer the problem: learn the math but only after learning the concepts and methodological considerations that give it context. With this as a starting point, Understanding Political Science Statistics asks students to consider how to address a research problem conceptually before being led to the appropriate formula. Throughout, Galderisi looks at problems through a lens of "observations and expectations," which can be applied to myriad statistical techniques, both descriptive and inferential. This approach links the answers researchers get from their individual data analysis to the research designs and questions from which these analyses are derived. By emphasizing the underlying logic of statistical analysis for greater understanding and drawing on applications and examples from political science (including law), the book illustrates how students can apply statistical concepts and techniques in their own research, in future coursework, and simply as an informed consumer of numbers in public discourse. The following features help students master the material: Legal and Methodological sidebars highlight key concepts and provide applied examples on law, politics, and methodology; End-of-chapter exercises allow students to test their mastery of the basic concepts and techniques along the way; A Sample Solutions Guide provides worked-out answers for odd-numbered exercises, with all answers available in the Instructor’s Manual; Key Terms are helpfully called out in both Marginal Definitions and a Glossary; A Companion Website (www.routledge.com/cw/galderisi) with further resources for both students and instructors; A diverse array of data sets include subsets of the ANES and Eurobarometer surveys; CCES; US Congressional district data; and a cross-national dataset with political, economic, and demographic variables; and Companion guides to SPSS and Stata walk students through the procedures for analysis and provide exercises that go hand-in-hand with online data sets.
Book Synopsis Statistics for Political Analysis by : Theresa Marchant-Shapiro
Download or read book Statistics for Political Analysis written by Theresa Marchant-Shapiro and published by CQ Press. This book was released on 2014-01-15 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics are just as vital to understanding political science as the study of institutions, but getting students to understand them when teaching a methods course can be a big challenge. Statistics for Political Analysis makes understanding the numbers easy. The only introduction to statistics book written specifically for political science undergraduates, this book explains each statistical concept in plain language—from basic univariate statistics and the basic measures of association to bivariate and multivariate regression—and uses real world political examples. Students learn the relevance of statistics to political science, how to understand and calculate statistics mathematically, and how to obtain them using SPSS. All calculations are modeled step-by-step, giving students needed practice to master the process without making it intimidating. Each chapter concludes with exercises that get students actively applying the steps and building their professional skills through data calculation, analysis, and memo writing.
Book Synopsis Foundations of Statistics for Data Scientists by : Alan Agresti
Download or read book Foundations of Statistics for Data Scientists written by Alan Agresti and published by CRC Press. This book was released on 2021-11-22 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.
Book Synopsis Introduction to Data Science for Social and Policy Research by : Jose Manuel Magallanes Reyes
Download or read book Introduction to Data Science for Social and Policy Research written by Jose Manuel Magallanes Reyes and published by Cambridge University Press. This book was released on 2017-09-21 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
Book Synopsis Quantitative Social Science by : Kosuke Imai
Download or read book Quantitative Social Science written by Kosuke Imai and published by Princeton University Press. This book was released on 2021-03-16 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
Book Synopsis Statistics and Analysis of Scientific Data by : Massimiliano Bonamente
Download or read book Statistics and Analysis of Scientific Data written by Massimiliano Bonamente and published by Springer. This book was released on 2016-11-08 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text. • end-of-chapter summary boxes, for easy reference. As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.
