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Statistical Rules of Thumb (Wiley Series in Probability and Statistics) | 
 enlarge | Author: Gerald Van Belle
Publisher: Wiley-Interscience
Category: Book
List Price: $59.95
Buy New: $44.43
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Rating:  8 reviews
Sales Rank: 187180
Media: Paperback
Edition: 2
Pages: 272
Number Of Items: 1
Shipping Weight (lbs): 1
Dimensions (in): 9.2 x 6.1 x 0.2
ISBN: 0470144483
Dewey Decimal Number: 519.5
EAN: 9780470144480
ASIN: 0470144483
Publication Date: September 2, 2008
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
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Amazon.com Review
Good scientists learn early on not to do everything by the book. Respected statistician Gerald Van Belle has compiled the unpublished wisdom of his profession in the invaluable Statistical Rules of Thumb. Those mathematicians involved in statistical work will applaud its clarity and organization, while other scientists will find their experimental design and analysis vastly improved by its suggestions. Each of the 99 rules has a brief introduction, a simple statement of the rule, illustrations, theoretical underpinnings, and extensions. Topics covered include covariation, design, consultation, epidemiology, and data representation. Van Belle is providing Web support for this ongoing project, so we can expect to see even greater breadth and refinement as it develops. --Rob Lightner
Product Description
Statistical Rules of Thumb, Second Edition compiles simple rules that are widely applicable, robust, and elegant, and each captures key statistical concepts. This handbook provides a framework for considering statistical questions such as sample size and design of experiments. Explaining the justification for each rule, this book conveys the various possibilities that statisticians must think of when designing and conducting a study or analyzing its data. It provides a framework for considering such aspects of statistical work such as: randomness and statistical models; sample size; covariation; epidemiology; environmental studies; designing, conducting, and analyzing studies; words, tables, and graphs; and consulting. New rules of thumb are included such as: Sample size for ratios of means; Very non-significant P-values are very significant; Dichotomize continuous variables for odds ratio analysis; and Correlations need to be substantial to gain advantage in ANCOVA. Some rules have been revised for the new edition, i.e. sample size for relative risk and sample size for percentage change. In addition, the references have been completed updated and expanded.
A related website www.vanbelle.org provides additional rules, author presentations and more.
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| Customer Reviews: Read 3 more reviews...
great idea, great reference book January 23, 2008
Michael R. Chernick (Holland PA)
28 out of 28 found this review helpful
Gerald van Belle is a biostatistician and professor at the University of Washington. He has coauthored an excellent text on biostatistics with Lloyd Fisher. In this delightful and clearly written text van Belle provides 99 rules of thumb based on his vast experience as a consultant and researcher in statistics and biostatistics. For a statistician or a student of statistics along with the term "rule of thumb" one thinks of the three sigma rule or the use of range divided by sample size as a quick estimate of standard error of the mean. But this text is much more than a compilation of such simple rules. Professor van Belle organizes the book into topical chapters on sample size determination, covariation, epidemiology, environmental studies, design, conduct and analysis of experiments, tables and graphics, and consulting. Each rule is put into proper context and is justified with mathemetical theorems or empirical evidence.
Some of the rules are more like guidance for proper approaches to problems. For example in reviewing the basics in chapter 1 van Belle discusses the linear model in terms of the key assumptions of independence, equal variance and normality. The rule of thumb in section 1.4 states that assumptions should be considered in the order (1) independence, (2) equal variance and (3) normality. Van Belle explains this order by showing that the inferences are far more sensitive to violations in the independence assumption than in either the assumption of equal variance or the assumption of normality. As a statistician, I am aware of the sensitivity to correlation and the fact that variances need to differ by a factor of nearly four before results are seriously affected. Also when the data do not fit the normal distribution we have the nonparametric alternatives based on ranks. Nevertheless,in practice it is easiest and routine to test normality first, variances second and correlation becomes an afterthought. In some situations this may be okay since we may have good reason to believe that the observations were generated independently. But the rule is a good practical guidance. If you question all three assumptions it makes sense to test them in the order van Belle is suggesting.
Other practical advice of this type include the following rules of thumb:
1. Start with the Poisson to model incidence or prevalence.
2. Begin with the exponential model for time to event data.
3. Begin with two exponentials to compare two survival distributions.
4. Begin with the lognormal distribution in environmental studies.
These rules are not meant to suggest that simple models always work or even that they work in the majority of case. It is just that it is best to start simple and let the analysis and diagnostics tell you when more complicated models are needed.
This book will be a great guide for statistical practitioners and a terrific reference for professional and consulting statisticians. The references suppoting the rules are as valuable as the rules themselves.
Great value August 9, 2007
Vincent Vinh-hung
5 out of 5 found this review helpful
A very welcome book. Packed full of useful information in a very readable form. I ordered it for the one and half page about "Overlapping confidence intervals do not imply nonsignificance". Have been overjoyed discovering the rest.
Extremely helpful and very readible February 25, 2007
N. Jenkins (Raleigh, NC)
5 out of 5 found this review helpful
Sometimes you don't want to see a lot of "scary math notation" -- you just want to know what a concept is and how to apply it. This book meets that desire. It takes all the theoretical math concepts and explains them in very readable and accessible language so that you won't have post-traumatic flashbacks to your college statistics days.
This book provides concrete and practical advice on how to use statistical methods and how to make sure that you are using them correctly. The very first chapter (which you can read online) talks about sample size and provides simple and equations to use to design an experiment that will give you statistically valid results. That chapter is worth the purchase price itself.
Between the quality of the information, and the ease of reading, this book has got to be one of the best books out there for those who shudder at the mere mention of statistics.
 Practical advice February 12, 2003
12 out of 12 found this review helpful
This is a useful book for the working statistician or consultant. Many questions arise in practice that are never covered in traditional textbooks, and with experience an applied statistician learns "rules of thumb". Here is a text that nicely organizes some of the most common questions and problems and design considerations, with solid practical advice. This is not a text for a course (unless a course in consulting), but would serve an applied researcher or statistician well.
Excellent Book - though not for the uninitiated January 9, 2003
38 out of 39 found this review helpful
Excellent reference for statisticians. Only two complaints:
1) In many instances, wording is not clear - you have to really pick sentences apart to figure out what the author meant.
2) Reasons for a particular rule sometimes leave you wanting. But at least you're introduced to the concept and can look elsewhere for assistance in understanding.Also, the title might lead some non-statisticans to think that they can pick this book up and learn how to plug and chug in all sorts of situations. This is not the case.
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