Learn how to conduct political research with R, the open source programming language and software environment for statistical computing and graphics.

With this new, comprehensive workbook, An R Companion to Political Analysis, students 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 aided by the use of many annotated and labeled screen shots, as well as many end-of-chapter exercises, allowing students to apply their new skills.

The student resources site includes:

• Datasets used in An R Companion to Political Analysis, Second Edition
• Tables and Figures from the book available to strengthen understanding of key terms and concept

​Acknowledgments

We gratefully acknowledge Philip H. Pollock III and Barry Edwards for writing an excellent text and creating the materials on this site.