R for political data science: a practical guide/ Francisco Urdinez, Andres Cruz.

Includes Bibliographical references and index.

"This 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. This book is divided into 3 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"-- Provided by publisher.