Comparing groups - Info and Reading Options
randomization and bootstrap methods using R
By Andrew Zieffler
"Comparing groups" was published by Wiley in 2011 - Hoboken, N.J, it has 298 pages and the language of the book is English.
“Comparing groups” Metadata:
- Title: Comparing groups
- Author: Andrew Zieffler
- Language: English
- Number of Pages: 298
- Publisher: Wiley
- Publish Date: 2011
- Publish Location: Hoboken, N.J
“Comparing groups” Subjects and Themes:
- Subjects: ➤ Psychology - R (Computer program language) - Distribution (Probability theory) - Random data (Statistics) - Data processing - Stichprobe - Zufallsauswahl - Bootstrap (Statistics) - R (Programm) - SOCIAL SCIENCE / Statistics - Statistik - Bootstrap (statistics) - Psychology, data processing - Programming languages (electronic computers) - Distribution (probability theory)
Edition Specifications:
- Pagination: xxxii, 298 p.
Edition Identifiers:
- The Open Library ID: OL27025297M - OL19835658W
- Online Computer Library Center (OCLC) ID: 682892487
- Library of Congress Control Number (LCCN): 2010054064
- ISBN-13: 9780470621691
- ISBN-10: 0470621699
- All ISBNs: 0470621699 - 9780470621691
AI-generated Review of “Comparing groups”:
"Comparing groups" Description:
The Open Library:
"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"--
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