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An R Companion to Political Analysis

An R Companion to Political Analysis

Third Edition

July 2022 | 416 pages | CQ Press
The Third Edition of An R Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards teaches your students to conduct political research with R, the open-source programming language and software environment for statistical computing and graphics. This workbook offers the same easy-to-use and effective style as the other software companions to the Essentials of Political Analysis, tailored for R. With this comprehensive workbook, students analyze research-quality data to learn descriptive statistics, data transformations, bivariate analysis (such as cross-tabulations and mean comparisons), controlled comparisons, correlation and bivariate regression, interaction effects, and logistic regression. The clear explanations and instructions are aided by the use of many annotated and labeled screen shots, as well as QR codes linking to demonstration videos. The many end-of-chapter exercises allow students to apply their new skills.

The Third Edition includes new and revised exercises, along with new and updated datasets from the 2020 American National Election Study, an experiment dataset, and two aggregate datasets, one on 50 U.S. states and one based on countries of the world. A new structure helps break up individual elements of political analysis for deeper explanation while an updated suite of R functions makes using R even easier. Students will gain valuable skills learning to analyze political data in R.
Chapter 1: Using R for Data Analysis
Chapter 2: Descriptive Statistics
Chapter 3: Creating and Transforming Variables
Chapter 4: Making Comparisons
Chapter 5: Graphing Relationships and Describing Patterns
Chapter 6: Random Assignment and Sampling
Chapter 7: Making Controlled Comparisons
Chapter 8: Foundations of Statistical Inference
Chapter 9: Hypothesis Tests with One or Two Samples
Chapter 10: Chi-Square Test and Analysis of Variance
Chapter 11: Correlation and Bivariate Regression
Chapter 12: Multiple Regression
Chapter 13: Analyzing Regression Residuals
Chapter 14: Logistic Regression
Chapter 15: Doing Your Own Political Analysis