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Research Design and Statistical Analysis - Arnold D. Well

Research Design and Statistical Analysis

By: Arnold D. Well, Jr., Robert F. Lorch, Jerome L. Myers, Caren M. Rotello

Paperback | 28 January 2025 | Edition Number 4

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This fully updated fourth edition of Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The guiding philosophy is to provide a strong conceptual foundation so that readers can generalize to new situations they encounter in their research, including new developments in data analysis.

Key features include:

  • Emphasis on basic concepts such as sampling distributions, design efficiency, and expected mean squares, relating the research designs and data analyses to the statistical models that underlie the analyses.
  • Detailed instructions on performing analysis using both R and SPSS.
  • Pedagogical exercises mapped to key topic areas to support students as they review their understanding and strive to reach their higher learning goals.

Incorporating the analyses of both experimental and observational data, and with coverage that is broad and deep enough to serve a two-semester sequence, this textbook is suitable for researchers, graduate students and advanced undergraduates in psychology, education, and other behavioral, social, and health sciences.

The book is supported by a robust set of digital resources, including data files and exercises from the book in an Excel format for easy import into R or SPSS; R scripts for running example analysis and generating figures; and a solutions manual.

For student resources, view the Support Material tab

Industry Reviews

"Having worn out the 3rd edition to the point of disintegration, I was pleased to learn of this new edition. The authors have elevated the book to new heights by Rotello's lucid and precise expository narrative and the incorporation of R."

Chad Dube, Associate Professor of Psychology, University of South Florida, USA

"Exploring advanced statistical analysis alongside robust research design principles, this rigorous yet accessible text prepares graduate students for practical applications through real-world examples and R/SPSS integration - purpose-built for a full-year curriculum."

Michael J. Hautus, Professor of Psychology, University of Auckland, New Zealand

"Students of psychological methods must develop a skillset that allows them to design, conduct, and analyze data from research studies with the level of care required to arrive at sound statistical inference.Research Design and Statistical Analysis by Rotello, Myers, Well, and Lorch guides researchers in this journey by discussing the complex topics needed to develop these skills in a comprehensive, yet comprehensible, manner. Their approach uses clear and focused writing to build students' understanding of concepts ranging from the most basic research designs, descriptive statistics, and hypothesis testing methods to more complex matters, such as repeated-measures designs, the use of covariates, and contrast testing. I also appreciate how the authors introduce students to the use of statistical software packages, such as SPSS and R, in their work. Many textbooks provide code. However, it is much rarer that a textbook balances both computational instruction and the information needed to use statistical software packages in a responsible manner. By exposing students to the assumptions underlying design and analysis choices, as well as common errors in data analysis and inference, Rotello, Myers, Well, and Lorch give researchers insight into the issues they should be considering before making judgments with only a "point-and-click" summary of results. The third edition of the text was my first formal introduction to methods and over 10 years later, it's still the first book I reach for whether I am double-checking my methodological understanding of a complex topic in my own work or am recommending a must-have reference for an aspiring experimental researcher."

Ryan Guggenmos, Associate Professor of Accounting and Cramer Research Fellow, Darla Moore School of Business, University of South Carolina, USA

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