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Product Description
STATISTICAL SLEUTH is an innovative treatment of general statistical methods, taking full advantage of the computer, both as a computational and an analytical tool. The material is independent of any specific software package. In "The American Statistician" (February 2000, Vol. 54, No. 1), George Cobb commented, "What is new and different about Ramsey and Schafer's book, what makes it a 'larger contribution,' is that it gives much more prominence to modeling and interpretation of the sort that goes beyond the routine patterns." His students did "substantially better" on term papers based on the analysis of data. In the book, the focus is on a serious analysis of real case studies; on strategies and tools of modern statistical data analysis; on the interplay of statistics and scientific learning; and on the communication of results. With interesting examples, real data, and a variety of exercise types (conceptual, computational, and data problems), the authors get students excited about statistics.
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Customer Reviews
Most Helpful Customer Reviews
6 of 6 people found the following review helpful
Format:Hardcover
I am an ecologist (biologist) by profession and statistics is my dear hobby. I have read and used hundreds (maybe 1000) of text books on statistics and data analysis methods and I must say that "The Statistical Sleuth" is one of the best. In fact, I bought it because an earlier reviewer seemed to hate it! I was curious to see such a lousy book. The Statistical Sleuth is nothing but lousy: it is so well written that even the most difficult things (ANOVA, multiple regression analysis, etc.) are a piece of cake. The authors just do not repeat what others have said hundreds of times before them but present new ideas. The text is full of interesting and rarely seen examples which make you realize the value of statistics. What I like the best are clear "Displays" which clarify printouts of statistical programs and, for instance, statistical model selection. I simply love this book and I am sure many more readers would love it, too, if they only knew that such a great book exists!
1 of 1 people found the following review helpful
Format:Paperback
The more I read this book the more impressed I am with it. It presents a clear practical approach to data analysis that is not too top heavy with mathematical statistical theory but is nevertheless rigorous and insightful. As noted by a previous reviewer, the diagrams (displays) are a lesson in clarity. The way they are labelled directs your attention in such a way it's almost like watching an animation. A real joy! The data sets are included on a CD mounted on the inside front cover or you can alternatively download them as an R package from the R website (sleuth2) NOTE. Be careful you know which book you order. The SSM version is the student solution manual!!The Statistical Sleuth: A Course in Methods of Data Analysis (SSM) Very expensive for a 44 page pamphlet.
Most Helpful Customer Reviews on Amazon.com (beta)
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23 reviews
20 of 22 people found the following review helpful
Good concept, more care needed with datasets
5 Sep 2006
Format:Hardcover
I have taught using this text 5 times now. I like the concept very much. My goals are to teach the students how to choose appropriate statistical tests and how to write up their results professionally. I very much like the concept of "project" exercises with real data sets.
Unfortunately, many of the datasets contain faulty data. I doubt that I have a full list of example, but Chapter 2, Problem 23 supposedly contains percent change in fatalities in states that retained and did not retain 55 mile per hour speed limits between 1995 and 1996. Unfortunately, the data reported have nothing in common with the real data. For instance, there were 87 fatalities in Alaska in 1995 and 81 in 1996 leading to a 7% decrease. The number used in the text is a 29% decrease. Other examples include Chapter 8, Problem 20 which is admittedly an approximation but the authors did not read the scale on the New York Times graphic correctly which places the supposed outlier rather differently than if the correct scale for the data is used. In Chapter 11, problem 24, there is an excessively heavy grasshopper mouse among other errant species weights.
The concept is great, a few data entry errors can be an effective learning tool, but too many blatantly incorrect datasets that lead to conclusions diametrically opposed to the real data seems sloppy to me.
Unfortunately, many of the datasets contain faulty data. I doubt that I have a full list of example, but Chapter 2, Problem 23 supposedly contains percent change in fatalities in states that retained and did not retain 55 mile per hour speed limits between 1995 and 1996. Unfortunately, the data reported have nothing in common with the real data. For instance, there were 87 fatalities in Alaska in 1995 and 81 in 1996 leading to a 7% decrease. The number used in the text is a 29% decrease. Other examples include Chapter 8, Problem 20 which is admittedly an approximation but the authors did not read the scale on the New York Times graphic correctly which places the supposed outlier rather differently than if the correct scale for the data is used. In Chapter 11, problem 24, there is an excessively heavy grasshopper mouse among other errant species weights.
The concept is great, a few data entry errors can be an effective learning tool, but too many blatantly incorrect datasets that lead to conclusions diametrically opposed to the real data seems sloppy to me.
22 of 25 people found the following review helpful
An excellent graduate-level text
24 May 2000
Format:Hardcover
This is a superb text for graduate students or advanced undergraduates. The case studies are excellent, and the approach is innovative. The strength of the book is its coverage of regression models (linear algebra not used - a weakness if you want to program in Matlab, but ok for SPSS). The examples are drawn from Ecology (esp. Island biogeography), Evolutionary biology, geochemistry, environmental policy, medicine and law. There is something of interest for even the most diverse audience.
14 of 15 people found the following review helpful
Excellent resource for the non-specialist practitioner
3 Nov 2004
Format:Hardcover
During my professional life I was several times in the situation of having to do statistical analysis of some data. I also saw other colleagues struggle with the same situation and it seems that for someone without a formal training in statistics and a lot of practical experience this is a strange mixture of technical know-how, guess-work and pure superstition.
This is the book I've been looking for for years now, to learn how to do the job with a reasonable understanding of the choices involved and the assumptions that are made when using this or that tool. It is a wonderfully practical and clear exposition of the methods that are likely to be used by a practitioner to answer practical questions with the help of data - and definitely helps to avoid the uneasy feeling of having to apply some tool without really knowing what is going on.
This is the book I've been looking for for years now, to learn how to do the job with a reasonable understanding of the choices involved and the assumptions that are made when using this or that tool. It is a wonderfully practical and clear exposition of the methods that are likely to be used by a practitioner to answer practical questions with the help of data - and definitely helps to avoid the uneasy feeling of having to apply some tool without really knowing what is going on.
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