Author(s): Andrew S. Zieffler, Jeffrey R. Harring, Jeffrey D. Long
A hands-on guide to using R to carry out key  statistical practices ineducational and behavioral                sciences research

Computing has become an essential part of the day-to-day  practice of statistical work, broadening the types of             questions that can now be addressed by research scientists  applying newly derived data analytic techniques. Comparing                Groups: Randomization and Bootstrap Methods Using R  emphasizes the direct link between scientific research             questions and data analysis. Rather than relying on   mathematical calculations, this book focus on conceptual             explanations and the use of statistical computing in an   effort to guide readers through the integration of design,             statistical methodology, and computation to answer specific  research questions regarding group differences.


Utilizing the widely-used, freely accessible R software,   the authors introduce a modern approach to promote methods             that provide a more complete understanding of statistical   concepts. Following an introduction to R, each chapter is             driven by a research question, and empirical data analysis is used to provide answers to that question. These examples are             data-driven inquiries that promote interaction between statistical methods and ideas and computer application.             Computer code and output are interwoven in the book to   illustrate exactly how each analysis is carried out and how             output is interpreted. Additional topical coverage includes:

• Data exploration of one variable and multivariate  data
• Comparing two groups and many groups
• Permutation tests, randomization tests, and the  independent samples t-Test
• Bootstrap tests and bootstrap intervals
• Interval estimates and effect sizes
  

Throughout the book, the authors incorporate data from  real-world research studies as well aschapter problems that             provide a platform to perform data analyses. A related Web   site features a complete collection of the book's datasets             along with the accompanying codebooks and the R script files  and commands, allowing readers to reproduce the presented       output and plots.


Comparing Groups: Randomization and Bootstrap Methods   Using R is an excellent book for upper-undergraduate and             graduate level courses on statistical methods, particularlyin  the educational and behavioral sciences. The book also serves             as a valuable resource for researchers who need a practical   guide to modern data analytic and computational methods.