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11 of 12 people found the following review helpful
5.0 out of 5 stars An essential reference, June 9, 2004
This review is from: Statistical Intervals: A Guide for Practitioners (Hardcover)
"Statistical Intervals" has for years been a valuable tool in my professional work, which focuses on environmental statistics. Hahn & Meeker's discussion of how to interpret various intervals--confidence, tolerance, prediction--first opened my eyes to the ubiquity and utility of these techniques. I since have found it worthwhile to have a working knowledge of them all; that would scarcely have been possible without having such a handy reference.

The tables are getting dog-eared and gray from use, especially A-12 (factors for computing Normal distribution one-sided tolerance bounds), in testimony to the frequency I refer to them. The book also contains extensive graphics for estimating intervals and for determining sample sizes: these typically obviate any need to refer to tables or do the computations. There are some neat formulas, clearly described, that one can easily implement in a spreadsheet. These all appear in other texts and journal articles, but having them all in one place, well organized, makes them particularly worthwhile.

This is, indeed, a reference: a statistical "cookbook" if you will (intended in a positive sense, not pejoratively!). This means you will find little theoretical justification for any of the material. For each technique expect to find a clear definition, lucid descriptions, discussions of how to use any supporting formulas, graphs, or tables, all followed by a clear worked example. Of course there's an extensive bibliography if your theoretical curiosity is piqued.

One common technique you will not find (although it is mentioned and references provided) is computing statistical intervals for linear regression analysis. This subject, however, is covered well in other books (such as Draper and Smith's Applied Regression Analysis), so the omission does no harm and helps keep the book to a manageable 400 pages or so.

There are some obscure applications you will not find, in part because they were only under development at the time this book was written. For instance, there is a specialized (but widely applied) theory of "k best of m" prediction limits that is used in groundwater monitoring. For such specialized applications you will have to go elsewhere (such as Robert Gibbons' book on "Statistical Methods for Groundwater Monitoring"). Nevertheless, Hahn and Meeker do a very good job of covering the most widely used applications of statistical intervals.

I do not recollect ever finding a mathematical error or even a typographical error. Over the years I have also checked, and completely verified, the entries in several of the key tables. All in all, this book is remarkably clean and error free.

(This review is based on the 1991 edition; I do not know whether there have been further editions.)
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