A hands-on guide to using R to carry out key statistical practices in educational and behavioral sciences researchComputing 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 dataComparing two groups and many groupsPermutation tests, randomization tests, and the independent samples t-TestBootstrap tests and bootstrap intervalsInterval estimates and effect sizesThroughout 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.
Author(s): Andrew S. Zieffler, Jeffrey R. Harring, Jeffrey D. Long
Edition: 1
Publisher: John Wiley & Sons
Year: 2011
Language: English
Pages: 331
Tags: Библиотека;Компьютерная литература;R;
CoverPage......Page 1
FrontMatter......Page 2
TitlePage......Page 4
CopyRight......Page 5
Contents......Page 6
List of Figures......Page 14
List of Tables......Page 22
Foreword......Page 24
Preface......Page 26
Acknowledgements......Page 32
ch01 AN INTRODUCTION TO R......Page 34
ch02 DATA REPRESENTATION AND PREPARATION......Page 54
ch03 DATA EXPLORATION: ONE VARIABLE......Page 82
ch04 EXPLORATION OF MULTIVARIATE DATA: COMPARING TWO GROUPS......Page 100
ch05 EXPLORATION OF MULTIVARIATE DATA: COMPARING MANY GROUPS......Page 128
ch06 RANDOMIZATION AND PERMUTATION TESTS......Page 150
ch07 BOOTSTRAP TESTS......Page 172
ch08 PHILOSOPHICAL CONSIDERATIONS......Page 206
ch09 BOOTSTRAP INTERVALS AND EFFECT SIZES......Page 214
ch10 DEPENDENT SAMPLES......Page 240
ch11 PLANNED CONTRASTS......Page 262
ch12 UNPLANNED CONTRASTS......Page 288
References......Page 320