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Statistics as Principled Argument: Psychology Press & Routledge Classic Editions

Autor Robert P. Abelson
en Limba Engleză Paperback – 3 noi 2025
In Statistics as Principled Argument, first published in 1995, Robert P. Abelson exposes the often-overlooked problems in quantitative data interpretation, and the challenge of presenting the data in terms of a coherent narrative about one's research. This classic edition offers a new introduction which views Abelson's work through a contemporary lens, highlighting how his teachings remain vitally relevant today.
The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Statistical methods are discussed, but with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t-tests, and simple issues of research design. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.
This remarkably engaging read is filled with fascinating real-life (and real research) examples rather than simply recipes for analysis. Abelson’s insights generate true interest for beginning graduate students and seasoned researchers alike, and will be invaluable to students, scholars, researchers, and practitioners who use statistics within their research.
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Specificații

ISBN-13: 9781041017271
ISBN-10: 1041017278
Pagini: 242
Ilustrații: 2
Dimensiuni: 152 x 229 x 14 mm
Greutate: 0.45 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria Psychology Press & Routledge Classic Editions

Locul publicării:Oxford, United Kingdom

Public țintă

Academic, Postgraduate, Professional Reference, and Undergraduate Advanced

Notă biografică

Robert P. Abelson was a professor in the psychology and political science departments at Yale University. He made foundational contributions to social psychology, political psychology, and cognitive science, as well as important contributions to statistics.

Cuprins

Preface to the Classic Edition by Lynn C. Miller and Stephen J. Read  Preface to the 1995 edition  Abelson’s Laws  1. Making Claims with Statistics  2. Elementary Arguments and the Role of Chance  3. Magnitude of Effects  4. Styles of Rhetoric  5. On Suspecting Fishiness  6. Articulation of Results: Ticks and Buts  7. Generality of Effects  8. Interestingness of Argument  9. Credibility of Argument

Descriere

In Statistics as Principled Argument, first published in 1995, delved into the often-dismissed problems of interpreting quantitative data and then presented them in the context of a coherent story about one's research. This classic edition offers a new introduction situating Abelson's work through a contemporary lens.

Recenzii

“Everyone doing research or planning to do research should read this book. You will be surprised at how much you will learn.”                                                                           - Psychological Science                                                                                                  
“The book itself is the best demonstration of the validity of Abelson’s thesis. It proves that statistical issues can be addressed in an articulate, interesting, entertaining and persuasive way.”                                                                                                                   - British Journal of Mathematical & Statistical Psychology
“Abelson has, in brief, produced a thought-provoking synthesis of the woes and promises of much modern  sychological statistics.”                                                            - British Journal of Psychology

"This book helps the advanced reader to think more capably about statistics and research. The reader will benefit from Abelson's expertise."
Association for Psychological Studies
"The book itself is the best demonstration of the validity of Abelson's thesis. It proves that statistical issues can be addressed in an articulate, interesting, entertaining and persuasive way."
British Journal of Mathematical & Statistical Psychology
"Abelson has, in brief, produced a thought-provoking synthesis of the woes and promises of much modern psychological statistics..."
British Journal of Psychology
"This volume is filled with the things that one is never taught but, one hopes, learns later....provides a useful capstone for anyone who concludes his/her formal training in statistics and is now simply a user....a pleasure."
Chance
"It is frequently of interest to hear about the statistical approaches and (sometimes) mistakes that investigators fall prey to in the field of psychology. The delightful book under review gives insights and cogent discussions of both approaches and mistakes."
Journal of Quality Technology
"Have you ever considered taking a statistics book to read at the beach or pool? Probably not. This delightful book may change all that....Instead of discussing the various statistical techniques and how to compute them, the author focuses on an overall perspective on what the investigator who uses statistical method is doing. His central theme is that statistical analysis is a tool for presenting a principled argument, meaning a credible argument that is truly based on data. ...Everyone doing research or planning to do research should read this book. You will be surprised at how much you will learn."

Psychological Science
"This is a refreshing exposition of the real story of how to use statistics, a story generally neglected in standard texts. Apart from its wisdom and technical competence, it is a sheer pleasure to read--graceful, witty, and informal. I recommend it highly for advanced undergraduate and graduate students in the social and biological sciences, their teachers, and practicing researchers in all fields who use statistics."
Jacob Cohen
New York University; Author, Applied Multiple Regression/Correlation Analysis