This book provides a narrative of how R can be useful in the analysis of public administration, public policy, and political science data specifically, in addition to the social sciences more broadly. It can serve as a textbook and reference manual for students and independent researchers who wish to use R for the first time or broaden their skill set with the program. While the book uses data drawn from political science, public administration, and policy analyses, it is written so that students and researchers in other fields should find it accessible and useful as well. By the end of the first seven chapters, an entry-level user should be well acquainted with how to use R as a traditional econometric software program. The remaining four chapters will begin to introduce the user to advanced techniques that R offers but many other programs do not make available such as how to use contributed libraries or write programs in R. The book details how to perform nearly every task routinely associated with statistical modeling: descriptive statistics, basic inferences, estimating common models, and conducting regression diagnostics. For the intermediate or advanced reader, the book aims to open up the wide array of sophisticated methods options that R makes freely available. It illustrates how user-created libraries can be installed and used in real data analysis, focusing on a handful of libraries that have been particularly prominent in political science. The last two chapters illustrate how the user can conduct linear algebra in R and create simple programs. A key point in these chapters will be that such actions are substantially easier in R than in many other programs, so advanced techniques are more accessible in R, which will appeal to scholars and policy researchers who already conduct extensive data analysis. Additionally, the book should draw the attention of students and teachers of quantitative methods in the political disciplines.

R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work. The book has 16 chapters and is organized in three sections. The first, on the use of R, is for those users who are learning R or are migrating from another software. The second section, on econometric models, covers OLS, binary and survival models, panel data, and causal inference. The third section is a data science toolbox of some the most useful tools in the discipline: data imputation, fuzzy merge of large datasets, web mining, quantitative text analysis, network analysis, mapping, spatial cluster analysis, and principal component analysis. Key features: Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R Provides a step-by-step guide that you can replicate using your own data Includes exercises in every chapter for course use or self-study Focuses on practical-based approaches to statistical inference rather than mathematical formulae Supplemented by an R package, including all data As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.

Teach your students to conduct political research using R, the open source programming language and software environment for statistical computing and graphics. An R Companion to Political Analysis offers the same easy-to-use and effective style as the best-selling SPSS and Stata Companions. The all-new Second Edition includes new and revised exercises and datasets showing students how to analyze research-quality data to learn descriptive statistics, data transformations, bivariate analysis (cross-tabulations and mean comparisons), controlled comparisons, statistical inference, linear correlation and regression, dummy variables and interaction effects, and logistic regression. The clear explanation and instruction is accompanied by annotated and labeled screen shots and end-of-chapter exercises to help students apply what they have learned. "Students will love this book, as will their teachers." – Courtney Brown, Emory University

"Pollock and Edwards explain the nuts-and-bolts of research design and data analysis in a clear and concise style. The Essential of Political Analysis is an intuitive introduction to complex material, replete with examples from the political science literature that add relevance to statistical concepts. This text offers students an excellent balance between the technical and the practical." —Francis Neely, San Francisco State University Gain the skills you need to conduct political analysis and critically assess statistical research. In this Sixth Edition of The Essentials of Political Science, bestselling authors Philip H. Pollock III and Barry C. Edwards build students’ analytic abilities and develop their statistical reasoning with new data, fresh exercises, and accessible examples. This brief, accessible guide walks students through the essentials—measuring concepts, formulating and testing hypotheses, describing variables—while using key terms, chapter-opening objectives, over 80 tables and figures, and practical exercises to get them using and applying their new skills. Using SPSS, STATA or R? Discounted package deals available with Philip H. Pollock’s companion workbooks. . Give your students the SAGE edge! SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning.

R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work. The book has 16 chapters and is organized in three sections. The first, on the use of R, is for those users who are learning R or are migrating from another software. The second section, on econometric models, covers OLS, binary and survival models, panel data, and causal inference. The third section is a data science toolbox of some the most useful tools in the discipline: data imputation, fuzzy merge of large datasets, web mining, quantitative text analysis, network analysis, mapping, spatial cluster analysis, and principal component analysis. Key features: Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R Provides a step-by-step guide that you can replicate using your own data Includes exercises in every chapter for course use or self-study Focuses on practical-based approaches to statistical inference rather than mathematical formulae Supplemented by an R package, including all data As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.

Teach your students to conduct political research using R, the open source programming language and software environment for statistical computing and graphics. An R Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards offers the same easy-to-use and effective style as the best-selling SPSS and Stata Companions. The all-new Second Edition includes new and revised exercises and datasets showing students how to analyze research-quality data to learn descriptive statistics, data transformations, bivariate analysis (cross-tabulations and mean comparisons), controlled comparisons, statistical inference, linear correlation and regression, dummy variables and interaction effects, and logistic regression. The clear explanation and instruction is accompanied by annotated and labeled screen shots and end-of-chapter exercises to help students apply what they have learned.

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.