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In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. 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. Particular statistical methods are discussed, 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. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.
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Table of Contents

Contents: Preface. Abelson's Laws. Making Claims With Statistics. Elementary Arguments and the Role of Chance. Magnitude of Effects. Styles of Rhetoric. On Suspecting Fishiness. Articulation of Results: Ticks and Buts. Generality of Effects. Interestingness of Argument. Credibility of Argument.

Reviews

"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

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