TY  - BOOK
AU  - Zieffler,Andrew
AU  - Harring,Jeffrey
AU  - Long,Jeffrey D.
ED  - Wiley InterScience (Online service)
TI  - Comparing groups: randomization and bootstrap methods using R 
SN  - 9781118063682
AV  - QA276.8 .Z53 2011
U1  - 519.5/4 22
PY  - 2011///
CY  - Hoboken, N.J.
PB  - Wiley
KW  - Bootstrap (Statistics)
KW  - Random data (Statistics)
KW  - Psychology
KW  - Data processing
KW  - R (Computer program language)
KW  - Distribution (Probability theory)
KW  - SOCIAL SCIENCE
KW  - Statistics
KW  - bisacsh
KW  - fast
KW  - Electronic books
N1  - Includes bibliographical references (pages 287-298); Front Matter -- An Introduction to R -- Data Representation and Preparation -- Data Exploration: One Variable -- Exploration of Multivariate Data: Comparing two Groups -- Exploration of Multivariate Data: Comparing Many Groups -- Randomization and Permutation Tests -- Bootstrap Tests -- Philosophical Considerations -- Bootstrap Intervals and Effect Sizes -- Dependent Samples -- Planned Contrasts -- Unplanned Contrasts -- References; ssh
N2  - "This book, written by three behavioral scientists for other behavioral scientists, addresses common issues in statistical analysis for the behavioral and educational sciences. Modern Statistical & Computing Methods for the Behavioral and Educational Sciences using R emphasizes the direct link between scientific research questions and data analysis. Purposeful attention is paid to the integration of design, statistical methodology, and computation to propose answers to specific research questions. Furthermore, practical suggestions for the analysis and presentation of results, in prose, tables and/or figures, are included. Optional sections for each chapter include methodological extensions for readers desiring additional technical details. Rather than focus on mathematical calculations like so many other introductory texts in the behavioral sciences, the authors focus on conceptual explanations and the use of statistical computing. Statistical computing is an integral part of statistical work, and to support student learning in this area, examples using the R computer program are provided throughout the book. Rather than relegate examples to the end of chapters, the authors interweave computer examples with the narrative of the book. Topical coverage includes an introduction to R, data exploration of one variable, data exploration of multivariate data - comparing two groups and many groups, permutation and randomization tests, the independent samples t-Test, the Bootstrap test, interval estimates and effect sizes, power, and dependent samples"--
UR  - http://dx.doi.org/10.1002/9781118063682
ER  -