Statistics as Principled Argument / Edition 1 available in Paperback
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.
|Publisher:||Taylor & Francis|
|Edition description:||New Edition|
|Product dimensions:||6.00(w) x 9.00(h) x 0.60(d)|
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.
Most Helpful Customer Reviews
A must read book for anyone who does or reads research in the social sciences, psychology, education, or similar fields. With almost no math or formulas, Abelson does not teach methods, he teaches thinking.
Really great book on statistics - not really for use as a main textbook, but as additional reading to help students understand the concepts and philosophy behind the tests they're using. This was one of the books in my grad school stats 2 class, and I'm really glad to have read it. People in my program love to quote this book; I hear "chance is lumpy" on a weekly basis :D