Quantitative Social Science: An Introduction

A textbook on data analysis and statistics for social science students, focusing on practical skills using R programming. It covers key concepts, exercises, and real-world data sets, making it an essential resource for undergraduate and graduate students in the field.

\n Format: Paperback / softback
\n Length: 432 pages
\n Publication date: 09 February 2018
\n Publisher: Princeton University Press
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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.

Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data science, this textbook provides hands-on instruction using R programming, not paper-and-pencil statistics. It includes more than forty data sets from actual research for students to test their skills on, covering data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools. A wealth of supplementary exercises, including coding challenges and case studies, help students apply the knowledge they have learned.

This textbook is an invaluable resource for anyone interested in learning data analysis and statistics for social science research, and it will be particularly useful for students in the social sciences and allied fields who are looking to gain a competitive edge in their field.

\n Weight: 914g\n
Dimension: 254 x 178 x 25 (mm)\n
ISBN-13: 9780691175461\n \n