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Quantitative Social Science - An Introduction (Hardcover)
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Quantitative Social Science - An Introduction (Hardcover)
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An introductory textbook on data analysis and statistics written
especially for students in the social sciences and allied fields
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* 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
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