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Main Title Comparing groups : randomization and bootstrap methods using R /
Author Zieffler, Andrew,
Other Authors
Author Title of a Work
Harring, Jeffrey,
Long, Jeffrey D.,
Publisher Wiley,
Year Published 2011
OCLC Number 682892487
ISBN 9780470621691 (hardback); 0470621699 (hardback)
Subjects Bootstrap (Statistics) ; Random data (Statistics) ; Psychology--Data processing ; R (Computer program language) ; Distribution (Probability theory) ; SOCIAL SCIENCE / Statistics
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
ELBM  QA276.8.Z53 2011 AWBERC Library/Cincinnati,OH 12/17/2012
Collation xxxii, 298 p. : ill. ; 25 cm.
Notes
Includes bibliographical references (p. 287-298).
Contents Notes
"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"--