Quantitative Social Science-轻识

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 und...

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.

Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science

Provides hands-on instruction using R programming, not paper-and-pencil statistics

Includes more than forty data sets from actual research for students to test their skills on

Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools

Features a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercises

Offers a solid foundation for further study

Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

Kosuke Imai is professor of politics and founding director of the Program in Statistics and Machine Learning at Princeton University.