The book makes the point of the title: Statistics should be presented as part of a principled argument. You are trying to make a case, and your argument will be better if it meets certain criteria; but which criteria are the right ones? In Statistics as Principled Argument, Abelson lists five criteria by which to judge a statistical argument. Magnitude How big is the effect? Articulation How precisely stated is it?

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The book makes the point of the title: Statistics should be presented as part of a principled argument. You are trying to make a case, and your argument will be better if it meets certain criteria; but which criteria are the right ones? In Statistics as Principled Argument, Abelson lists five criteria by which to judge a statistical argument. Magnitude How big is the effect?

Articulation How precisely stated is it? Generality How widely does it apply? Interesting How interesting is it? Credibility How believable is it? We can tell how big an effect is through various measures of effect size.

I can get into some of these in later article, but some of the common ones are correlation coefficients, the difference between two means, and regression coefficients.

Big effects are impressive. Small effects are not. How big is big depends on context, and on what we already know. But if it was a diet tested on rats, 10 ounces might be a lot.

Articulation is measured in what Abelson calls Ticks and Buts. The more ticks the better, the fewer buts the better. There are also blobs, which are masses of undifferentiated results. Blobs are, as you might have guessed, bad. Generality refers to how general an effect is. Does it apply to all humans everywhere?

That would be very general. Or does it apply only to left handed people who have posted 50 or more articles on AC? That would be pretty specific. Usually, more general effects are of greater value than more specific ones, but you should be sure that the study states how general it is. Interestingness is very hard to measure precisely, but one way is to say how different the reported effect size is from what we thought it would be.

For example, I once read a study that showed that Black people, on average, earn less than Whites. Upsetting, but not interesting. I would have thought that Black women earned much less than Whites! Finally, credibility. The more hard a result is to believe, the more stringent you have to be about the evidence supporting it. Extraordinary claims require extraordinary evidence. I specialize in helping graduate students and researchers in psychology, education, economics and the social sciences with all aspects of statistical analysis.

Many new and relatively uncommon statistical techniques are available, and these may widen the field of hypotheses you can investigate. Graphical techniques are often misapplied, but, done correctly, they can summarize a great deal of information in a single figure.

I can help with writing papers, writing grant applications, and doing analysis for grants and research. Specialties: Regression, logistic regression, cluster analysis, statistical graphics, quantile regression.

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## Statistics as Principled Argument

Abelson In this illuminating volume, Robert P. 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.

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## Statistics As Principled Argument.

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.

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## Book Review: Statistics as Principled Argument by Robert Abelson

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