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An ideal textbook for an introductory course on quantitative
methods for social scientists-assumes no prior knowledge of
statistics or coding Data Analysis for Social Science provides a
friendly introduction to the statistical concepts and programming
skills needed to conduct and evaluate social scientific studies.
Using plain language and assuming no prior knowledge of statistics
and coding, the book provides a step-by-step guide to analyzing
real-world data with the statistical program R for the purpose of
answering a wide range of substantive social science questions. It
teaches not only how to perform the analyses but also how to
interpret results and identify strengths and limitations. This
one-of-a-kind textbook includes supplemental materials to
accommodate students with minimal knowledge of math and clearly
identifies sections with more advanced material so that readers can
skip them if they so choose. Analyzes real-world data using the
powerful, open-sourced statistical program R, which is free for
everyone to use Teaches how to measure, predict, and explain
quantities of interest based on data Shows how to infer population
characteristics using survey research, predict outcomes using
linear models, and estimate causal effects with and without
randomized experiments Assumes no prior knowledge of statistics or
coding Specifically designed to accommodate students with a variety
of math backgrounds Provides cheatsheets of statistical concepts
and R code Supporting materials available online, including
real-world datasets and the code to analyze them, plus-for
instructor use-sample syllabi, sample lecture slides, additional
datasets, and additional exercises with solutions Looking for a
more advanced introduction? Consider Quantitative Social Science by
Kosuke Imai. In addition to covering the material in Data Analysis
for Social Science, it teaches diffs-in-diffs models, heterogeneous
effects, text analysis, and regression discontinuity designs, among
other things.
A tidyverse edition of the acclaimed textbook on data analysis and
statistics for the social sciences and allied fields Quantitative
analysis is an essential skill for social science research, yet
students in the social sciences and related areas typically receive
little training in it. Quantitative Social Science is a practical
introduction to data analysis and statistics written especially for
undergraduates and beginning graduate students in the social
sciences and allied fields, including business, economics,
education, political science, psychology, sociology, public policy,
and data science. Proven in classrooms around the world, this
one-of-a-kind textbook engages directly with empirical analysis,
showing students how to analyze and interpret data using the
tidyverse family of R packages. Data sets taken directly from
leading quantitative social science research illustrate how to use
data analysis to answer important questions about society and human
behavior. Emphasizes hands-on learning, not paper-and-pencil
statistics Includes 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 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
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
An ideal textbook for an introductory course on quantitative
methods for social scientists—assumes no prior knowledge of
statistics or coding Data Analysis for Social Science provides a
friendly introduction to the statistical concepts and programming
skills needed to conduct and evaluate social scientific studies.
Using plain language and assuming no prior knowledge of statistics
and coding, the book provides a step-by-step guide to analyzing
real-world data with the statistical program R for the purpose of
answering a wide range of substantive social science questions. It
teaches not only how to perform the analyses but also how to
interpret results and identify strengths and limitations. This
one-of-a-kind textbook includes supplemental materials to
accommodate students with minimal knowledge of math and clearly
identifies sections with more advanced material so that readers can
skip them if they so choose. Analyzes real-world data using the
powerful, open-sourced statistical program R, which is free for
everyone to use Teaches how to measure, predict, and explain
quantities of interest based on data Shows how to infer population
characteristics using survey research, predict outcomes using
linear models, and estimate causal effects with and without
randomized experiments Assumes no prior knowledge of statistics or
coding Specifically designed to accommodate students with a variety
of math backgrounds Provides cheatsheets of statistical concepts
and R code Supporting materials available online, including
real-world datasets and the code to analyze them, plus—for
instructor use—sample syllabi, sample lecture slides, additional
datasets, and additional exercises with solutions Looking for a
more advanced introduction? Consider Quantitative Social Science by
Kosuke Imai. In addition to covering the material in Data Analysis
for Social Science, it teaches diffs-in-diffs models, heterogeneous
effects, text analysis, and regression discontinuity designs, among
other things.
The Stata edition of the groundbreaking textbook on data analysis
and statistics for 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 business, economics, education, political science,
psychology, sociology, public policy, and data science.
Quantitative Social Science engages directly with empirical
analysis, showing students how to analyze data using the Stata
statistical software and interpret the results-it emphasizes
hands-on learning, not paper-and-pencil statistics. More than fifty
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
classrooms around the world, this one-of-a-kind textbook features
numerous additional data analysis exercises, and also comes with
supplementary teaching materials for instructors. Written
especially for students in the social sciences and allied fields,
including business, economics, education, psychology, political
science, sociology, public policy, and data science Provides
hands-on instruction using Stata, not paper-and-pencil statistics
Includes more than fifty 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
A tidyverse edition of the acclaimed textbook on data analysis and
statistics for the social sciences and allied fields Quantitative
analysis is an essential skill for social science research, yet
students in the social sciences and related areas typically receive
little training in it. Quantitative Social Science is a practical
introduction to data analysis and statistics written especially for
undergraduates and beginning graduate students in the social
sciences and allied fields, including business, economics,
education, political science, psychology, sociology, public policy,
and data science. Proven in classrooms around the world, this
one-of-a-kind textbook engages directly with empirical analysis,
showing students how to analyze and interpret data using the
tidyverse family of R packages. Data sets taken directly from
leading quantitative social science research illustrate how to use
data analysis to answer important questions about society and human
behavior. Emphasizes hands-on learning, not paper-and-pencil
statistics Includes 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 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
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
The Stata edition of the groundbreaking textbook on data analysis
and statistics for 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 business, economics, education, political science,
psychology, sociology, public policy, and data science.
Quantitative Social Science engages directly with empirical
analysis, showing students how to analyze data using the Stata
statistical software and interpret the results-it emphasizes
hands-on learning, not paper-and-pencil statistics. More than fifty
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
classrooms around the world, this one-of-a-kind textbook features
numerous additional data analysis exercises, and also comes with
supplementary teaching materials for instructors. Written
especially for students in the social sciences and allied fields,
including business, economics, education, psychology, political
science, sociology, public policy, and data science Provides
hands-on instruction using Stata, not paper-and-pencil statistics
Includes more than fifty 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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