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Statistics Using R introduces the most up-to-date approaches to R
programming alongside an introduction to applied statistics using
real data in the behavioral, social, and health sciences. It is
uniquely focused on the importance of data management as an
underlying and key principle of data analysis. It includes an
online R tutorial for learning the basics of R, as well as two R
files for each chapter, one in Base R code and the other in
tidyverse R code, that were used to generate all figures, tables,
and analyses for that chapter. These files are intended as models
to be adapted and used by readers in conducting their own research.
Additional teaching and learning aids include solutions to all
end-of-chapter exercises and PowerPoint slides to highlight the
important take-aways of each chapter. This textbook is appropriate
for both undergraduate and graduate students in social sciences,
applied statistics, and research methods.
Statistics Using Stata uses a highly accessible and lively writing
style to seamlessly integrate the learning of the latest version of
Stata (17) with an introduction to applied statistics using real
data in the behavioral, social, and health sciences. The text is
comprehensive in its content coverage and is suitable at
undergraduate and graduate levels. It requires knowledge of basic
algebra, but no prior coding experience. It is uniquely focused on
the importance of data management as an underlying and key
principle of data analysis. It includes a .do-file for each
chapter, that was used to generate all figures, tables, and
analyses for that chapter. These files are intended as models to be
adapted and used by readers in conducting their own research.
Additional teaching and learning aids include solutions to all
end-of-chapter exercises and PowerPoint slides to highlight the
important take-aways of each chapter.
Written in a clear and lively tone, Statistics Using IBM SPSS
provides a data-centric approach to statistics with integrated SPSS
(version 22) commands, ensuring that students gain both a deep
conceptual understanding of statistics and practical facility with
the leading statistical software package. With one hundred worked
examples, the textbook guides students through statistical practice
using real data and avoids complicated mathematics. Numerous
end-of-chapter exercises allow students to apply and test their
understanding of chapter topics, with detailed answers available
online. The third edition has been updated throughout and includes
a new chapter on research design, new topics (including weighted
mean, resampling with the bootstrap, the role of the syntax file in
workflow management, and regression to the mean) and new examples
and exercises. Student learning is supported by a rich suite of
online resources, including answers to end-of-chapter exercises,
real data sets, PowerPoint slides, and a test bank.
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