My professor suggested this book and deemed it the "Bible on Evidence". I bought it and it is. A great book that will clear up many of your questions. If you don't understand what your law professor is saying, this book will make it clearer.

I buy this book to help learn .NET to take MicroSoft tests. Did not know book is writen for beta .NET. I did not pass test since I learned from wrong version.

DO NOT BUY. Is old and no help.

Forget this book, unless you application the same as theirs.

This book provides an exellence big picture of .NET in developing an e-commerce website. It will definitely save you a lot of time in developing a website. It does not provide in detail on how do you implement it though. You would need specific books on asp.net and on VB.net or C# to complement it.

I reviewed this book for Technometrics in 1991. I would not recommend it for anyone! It is a cookbook of techniques that were selected by the author because he viewed them as useful in engineering or manufacturing. Almost no attention is given to the fundamental concepts and theory underlying the techniques.

Probability distributions are introduced without motivation giving the readers the misimpression that statistics is simply a set of tools to systematically apply. All the student needs to do is learn how to read a given set of statistical tables. This is a terrible impression to give in a first course and it makes for a very dry and boring course!

Analysis of variance is given some treatment in chapter 9 on experimental designs but the important topic of robust designs that had emerged in the 1980s specifically for manufacturing processes inspired by the work of Taguchi is not even mentioned.

Another problem with the book is the order in which topics are presented. Rather than being the 5th chapter, Chapter 5 on data gathering and problem solving should come first to motivate the methods and lead in to a discussion of probability distributions. Furthermore moments such as the skewness and kurtosis are discussed with reference to the Normal distribution before any formal presentation of the distribution and its properties. Sequential test procedures are thrown out to the student before even defining what a formal statistical hypothesis test is. Earlier classic books such as Bowker and Lieberman (1972) "Engineering Statistics" 2nd Edition or the two volumes of Johnson and Leone (1977)"Statistics and Experimental Design in Engineering and Physical Sciences" serve the students much better even if they do not have a strong background in mathematics.

Other problems with the book include vague definitions of such terms as central tendency, variance, skewness and kurtosis. Distributions such as the Normal distribution are referred to without a formal definition. Probability density functions are introduced without development of any probability concepts. There is a very poor description of the binomial distribution and its relationship to the binomial expansion.

In Chapter 2 operating characteristic curves are introduced but there is no discussion of power of tests. Hypothesis testing and type I and type II error probabilties are deferred to Chapter 8. In short this is book without foundation and will be very confusing to the audience it professes to teach. It can be used as a cookbook for those who want to run statistical procedures without any basic understanding, a very dangerous venture.

I have many more examples of specific problems with the book. If you want to see the details, go to the library and read my review on page 356 of Volume 33 of Technometrics (the August 1991 issue).