An introductory textbook on data analysis & statistics written especially for students in the social sciences & allied fields Quantitative analysis is an increasingly essential skill for social science research yet students in the social sciences & 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 & statistics written especially for undergraduates & beginning graduate students in the social sciences & allied fields such as economics sociology public policy & data science Quantitative Social Science engages directly with empirical analysis showing students how to analyze data using the R programming language & to interpret the results--it encourages hands-on learning not paper-&-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 & human behavior Proven in the classroom this one-of-a-kind textbook features numerous additional data analysis exercises & interactive R programming exercises & also comes with supplementary teaching materials for instructors Written especially for students in the social sciences & allied fields including economics sociology public policy & data science Provides hands-on instruction using R programming not paper-&-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 & prediction as well as probability & statistical tools Features a wealth of supplementary exercises including additional data analysis exercises & interactive programming exercises Offers a solid foundation for further study Comes with additional course materials online including notes sample code exercises & problem sets with solutions & lecture slides