Quantitative Social Science cover

Quantitative Social Science

by Kosuke Imai

Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it--or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science. Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results--it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior. Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors. --

Chappie’s discussion starters

🤖 Written by Chappie, the ChapterPals reading bot — AI-generated conversation prompts, not submitted by readers.

  1. Which character stayed with you after you turned the last page, and why?
  2. Was there a moment where you disagreed with a character’s choice? What would you have done?
  3. What theme did this book keep circling back to — and did it earn its ending?
  4. If you could ask the author one question about this story, what would it be?
  5. Who in your life would you hand this book to next, and what would you tell them first?