QuantitativeSocialScience

Quantitative analysis is an increasingly essential skill for social science research. However, students in the social sciences and related areas typically receive little training in it. Even if they do receive some training, it often comes in the form of statistics classes that offer few insights into their field.

To address this issue, the textbook "Quantitative Social Science" has been written specifically for undergraduates and beginning graduate students in the social sciences and allied fields such as economics, sociology, public policy, and data science. The book is a practical introduction to data analysis and statistics, providing hands-on instruction using the R programming language, rather than relying on paper-and-pencil statistics.

The book includes more than forty data sets taken directly from leading quantitative social science research. These data sets illustrate how data analysis can be used to answer important questions about society and human behavior. This approach encourages hands-on learning and engagement with empirical analysis.

This one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, making it ideal for classroom use. It covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools.

The book also offers a solid foundation for further study and comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides. If you are a student in the social sciences or related fields, this textbook is a valuable resource for developing your analytical skills.

作者简介

KosukeImaiisprofessorofpoliticsandfoundingdirectorofthePrograminStatisticsandMachineLearningatPrincetonUniversity.