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 Looking for a more accessible
introduction? Consider Data Analysis for Social Science by Elena
Llaudet and Kosuke Imai, which teaches from scratch and step-by-step
the fundamentals of survey research, predictive models, and causal
inference. It covers descriptive statistics, the difference-in-means
estimator, simple linear regression, and multiple linear regression.
Les mer
Produktdetaljer
ISBN
9781400885251
Publisert
2016
Utgiver
Vendor
Princeton University Press
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter