Introduction to Political Analysis in R

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A01=H. Whitt Kilburn
Author_H. Whitt Kilburn
Category=JMB
Category=JP
Category=PBT
Category=UFM
data science
data visualization tools
election forecasting
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
political data modeling applications
political science
quantitative research methods
spatial data analysis
statistics
text mining techniques
undergraduate curriculum

Product details

  • ISBN 9781032556581
  • Weight: 810g
  • Dimensions: 156 x 234mm
  • Publication Date: 31 Jul 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Introduction to Political Analysis in R is a comprehensive guide for students and researchers eager to delve into the intersection of data science, statistics, and political science. Aimed at equipping readers with the essential quantitative skills to analyze political data, the book bridges practical coding techniques in R with foundational statistical concepts, emphasizing real-world applications in politics.

The text adopts a progressive structure, beginning with the basics of R and data manipulation before advancing to more complex topics such as data visualization, spatial analysis, text analysis, and modeling. Through accessible language and engaging examples—ranging from U.S. election forecasting to global development trends—it demystifies complex analytical methods. Each chapter integrates coding exercises and real-world datasets to reinforce learning, fostering independent data analysis skills.

Designed for undergraduate political science majors, this book is also a valuable resource for anyone seeking to understand data-driven political analysis, whether for academic research, professional development, or personal curiosity.

Key features include:

  • Integrates data science and statistics with a political science focus, offering hands-on coding practice using the R programming language.
  • Provides real-world datasets and step-by-step exercises, enabling students to directly apply concepts to political phenomena such as gerrymandering.
  • Features a progressive chapter structure, progressing from foundational data handling to advanced methods like text analysis, spatial mapping, and linear modeling.
  • Emphasizes accessible coding for beginners, fostering self-sufficiency in data analysis without requiring prior statistical expertise.
  • Bridges theory and application with examples that engage students’ interest in politics while developing transferable analytical skills.

H. Whitt Kilburn is Associate Professor of Political Science, Grand Valley State University, Allendale, Michigan.

H. Whitt Kilburn is Associate Professor of Political Science, Grand Valley State University, Allendale, Michigan.

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