Parameter

I think this book has great potential. Unfortunately, it suffers from a few of the most fairly common Graduate Level text book problems.

Use of the 'et cetera' function, or a failure to work out examples. I'm not sure if I'm in a minority with this opinion, but I believe, after many years as a graduate student that examples should be worked on in their entirety. Unfortunately, this in not the case with this textbook. There are numerous places in this text where the authors reference, with great generality, pervious half-worked examples or formulas. Not only does this make the text sometimes difficult to follow, it also reduces the usefulness of the book as a self teaching tool.

The text also fails to include even some of the solutions to its exercises. I'm not sure why many authors fail to include even some of the solutions to their chapter exercises. In my opinion, I believe that this is a serious weakness in text. Most professors who teach graduate level courses create their own problem sets. By failing to include even partial solution sets, the authors minimizes or completely destroys any benefit of including exercises in the text (especially if you are not reading this text as part of a course). There is no benefit of working out exercises if you can not correct or even identify your mistakes.

If I had to have just one "Design of Experiments" book, I would not choose this one. Although there are many great things about this book, it is notoriously light on Split-Plot experiments. In fact, Split-plot experiments (which are very common) only receive a cursory mention. If you are looking for Books on Designs of experiments, I suggest you look at "Design and Analysis of Experiments" by Douglas Montgomery, or maybe even the older "Statistical Design and Analysis of Experiments" by Mason, Gunst, and Hess.

There are many ways one can judge a textbook. For graduate textbooks, the most important aspect one should look at is if they are worth keeping. Taking a graduate course in statistics generally means that one has chosen a career in statistics or a career with a significant statistical component in it. So the value of a textbook after graduate studies is an important consideration any instructor should give. It is pitiful that some of the textbooks from my own graduate studies are not worth a second reading, either because they lack modern topics or because they are mostly devoted to mechanical derivations.

Wu and Hamada (2000) is a superb textbook in this regard. The book is loaded with a number of most important modern topics in design of experiments, including robust parameter design, minimum aberration, designs with complex aliasing, and generalized linear models (p. xvii). These modern topics only receive some courteous treatment, if any at all, in most of design textbooks. The importance of these topics cannot be over-stated. It is impossible for an instructor to provide a detailed coverage of all the important topics in any design course. Practical problems often require the use of certain methods, which may or may not be touched in a design course. Therefore, we will often have to go back to our graduate textbooks to do some further reading. The comprehensive design tables in Wu and Hamada (2000)
also make this further learning process easier. For those who are doing research in the area after their graduate studies, Wu and Hamada (2000) is a necessity. Accessing design literature through journals is much more inconvenient and time-consuming. Wu and Hamada (2000) is also a suitable textbook for a design course for undergraduates majoring in statistics, or other areas of mathematical sciences.

If I can only own one design book, this is the one.

Jeff Wu got his Ph.D. in statistics from UC Berkeley. He started his career at the University of Wisconsin in Madison where he was influenced by George Box and was exposed to many important practical design problems. Jeff quickly established himself as a top notch theoretical statistician publishing some landmark papers in the Annals of Statistics. As his career developed at Wisconsin and later in Canada and at Michigan he made fundamental contributions to survey sampling and experimental design. This book is basically a sequel to the classic book by Box, Hunter and Hunter. It includes all aspects of experimental design and is very thorough in covering all the classical topics and the new area of robust design. It includes many recent advances by the authors (Wu and Hamada) in the 1990 and even the late 1990s (papers from 1997 and 1998 are referenced).

The book is intended for scientists and engineers as well as statisticians. The authors deliberately introduce the concepts gently, starting with a real problem and constructing and analyzing a design type considered in the chapter. This is done consistently from chapters 3-13.

They start with the simplest ideas and designs and build up. Chapter 1 deals with single factor experiments and Chapter 2 with experiments with more than one factor, starting with two. Section 1.1 provides an historical perspective which I find valuable. It leads to a classification of design problems that are distinct and they show how they arose in very different contexts. They do a good job of setting the stage for the remaining chapters. The categories are (1)Treatment Comparisons (the traditional agricultural experiment), (2) Variable Screening, (3) Response Surface Exploration, (4) System Optimization and (5) System Robustness. Although the theory of optimal designs is not covered in detail, the role of optimal designs is mentioned as is the early work of Kiefer (section 4.4.2)and reference to the recent book by Pukelsheim is given.

In Chapter 4 on fractional factorial experiments at two levels, concepts of resolution and aberration are clearly explained. I think it helps that the authors make these concepts concrete through the illustrative examples. I have often looked at standard design texts and found myself confused about the distinction between resolution III, IV and V designs.

There are several features that set this book apart from other books on design of experiments. Some attention is given to the one-factor-at-a-time approach. Most books ignore this commonly used approach and its many drawbacks. The authors explain its four main disadvantages and illustrate the problem with a design example. In my experience in industry, many engineers are not trained well in statistics and although it may seem clear to statisticians that one-at-a-time approaches overlook interactions or dependencies between variables, the engineers often do not. They see this approach as a way to simplify their search for the best operating conditions. I published an article in the mathematical modeling literature that also was intended to demonstrate the value of statistical design methods over the one-at-a-time approach. Latin square and Graeco-Latin Squares are covered as well as the more common factorial and fractional factorial designs. They also cover randomized blocks and balanced incomplete blocks. The concept of pairing (blocking) is well illustrated with a particular analysis of variance done both with and without pairing. Underlying assumptions are brought out and never hidden. The principles that are the basis for selection of fractional factorial designs are made explcit. Practical nonregular designs including the popular Plackett-Burman designs are well covered. Chapter 10 provides the basis and motivation for robust parameter designs. It also includes a discussion of the signal-to-noise ratio approach of Taguchi and describes some of its weaknesses. Chapter 11 looks at various performance measures for robust parameter design and compares several designs with respect to these parameters.

In the early chapters, the analysis of variance is presented clearly with all the required assumptions. Multiple comparison methods are discussed. Good references, both recent and old, are provided on each topic. My only disappointment was the omission of the recent resampling approaches to p-value adjustment due primarily to Westfall and Young.

Another interesting and unique aspect of the book is the presentation of Bayesian variable selection strategies. This introduces much of the interesting new work in Bayesian methods using the Markov Chain Monte Carlo methods.

Chapters 12 and 13 cover topics you will not find in other experimental design books. Chapter 12 deals with experiments to improve reliability and 13 with nonnormal data. Use of generalized linear models and transformation of variables is well covered in the book.

This book is a worthy sequel to Box, Hunter and Hunter. It is a great introductory book for experimental design courses and a great reference source for scientists, engineers and statisticians. It is already gaining in popularity.

Most people think that spectrum estimation is the same as FFT(Fast Fourier Transform) just because the FFT algorithm has beencelebrated for decades. Bretthorst looks at spectrum estimation from a statisticians point of view. Therefore his view, his examples and his reasoning appeal more to intuition than is usually the case in the electrical engineering text books. To be precise, his approach is Bayesian reasoning. Some people treat this kind of reasoning as heretic because it is based on an unorthodox understanding of probability. While most text books tell you that a probability is a long-run relative frequency, the "Bayesians" think of it as a degree-of-belief (or plausibility).

This sounds strange to you ? Yes it is. This book definitely is not in the mainstream. It evolved out of Bretthorst's PhD thesis (written under E.T. Jaynes, a Bayesian Guru) and it will not surprise you that such a book presents some new material instead of simply summing up well known material. Nevertheless, the book was also meant to be a tutorial introduction to the Bayesian approach. If you have been exposed to some advanced calculus courses, this might be an interesting introduction to statistics for you.

Anyway, this book is more than 10 years old now and in the meantime most people would recommend other tutorials into Bayesian statistic, for example the one by D. Sivia (ISBN 0-19-851889-7). END

I wish I had discovered this book long ago. It contains a systematic exposition of the Bayesian approach to the problem of detecting periodic signals. In addition to providing a clear framework for this problem, and many useful results, it is an excellent example of the Bayesian method at work. Just one of the many results obtained early in the book: the relation between the periodogram (which can be veiwed as a frequentist "statistic") and the Bayesian posterior for this problem is made clear.

What captivates me most about this textbook is its comprehensibility and clarity. It proves to be the impressive compendium work within Principles-and-Parameters (P&P) model. Moreover, its problem sets enhance your linguistic awareness by inviting you to think about controversial issues in the field. However, the second edition contains some errors in typography, which we do not see in the first edition. Another weakpoint of this book is that in the second edition the summary at the end of each section in each chapter is removed. In actuality, only the general summary for each chapter can be found, unlike the first edition. This is why it is not granted 5-star rating. To sum up, this introduction to transformational grammar (TG) is a very nice mix of theory and practice and does not try to overwhelm the reader with too many jargons and complicated explanations.

I got a linguistics BA in '78, and had mostly ignored the field since. Recently, I was trying to read Kayne's Parameters and Universals and realized there was too much I had forgotten, or never seen.

So I bought Ouhalla's book, and I have to say, I am very happy with it. It does an excellent job of presenting and explaining the endless jargon of linguistics. (Technical terms are in bold, and can actually be found in the index.) The presentation of phrase structure & transformations is clear and puts them in their historical/theoretical context. There follow 200 pages on principles & parameters, 100 on language variation, and the book ends with 60 pages on the Minimalist Program. Ouhalla does a good job at the end of each chapter of directing you to further reading. Ouhalla's writing style is effective and easy to read.

I recommend this book for what it is, an introduction to modern syntactic theory. Don't take it for an intro to linguistics as a whole. This book is quite approriate for those without linguistic training, but not for those without an interest in syntax.

Seems to be written for people with no background in designing experiments. Gives you a good start and gives you the basic information on Taguchi methods. A favorite of Engineering students since it is extremely easy to follow. Great first book for someone starting out with Design of Experiments. Covers the full problem solving process with DOE being a part of the process.

Minimal information is given regarding Classical DOE. If you have an academic or Engineering background and are interested in learning experimental designs other than Taguchi methods, then buy the "Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building" By: George E. P. Box, et al. -- the Classical DOE reference handbook for Engineers.

Maybe the most known and recurrently used Taguchi techniques are the Orthogonal Arrays for DOE; but they're not the only ones that Taguchi developed in order to achieve a quality product design. The Loss Function, the S/N ratio and the Tolerance Design are part of the "Robust Engineering" that consolidated Taguchi as the quality guru he is.

Many general DOE concepts are so well explained in this book that it represents a great introductory text to this subject. Nevertheless this is a Taguchi techniques book, not a complete DOE text, so it's possible that you'd like to look for "Design and Analysis of Experiments" by Douglas C. Montgomery.

This book is highly valuable if you want to understand the Taguchi philosophy for developing quality products and a must have for DOE beginners.

An excellent work that offers support for the tenets of Chomskyan linguistics. The book offers clear insights into the workings of the human mind and would serve well as a text in developmental psychology as well as for related courses in linguistics. The arguments are lucid and the subject matter is both fascinating and central to a more complete understating of language and the mind.

An excellent work that offers support for the tenets of Chomskyan linguistics. The book offers clear insights into the workings of the human mind and would serve well as a text in developmental psychology as well as for related courses in linguistics. The arguments are lucid and the subject matter is both fascinating and central to a more complete understating of language and the mind.

An excellent work that provides support for the tenets of Chomskyan linguistics. The book offers clear insights into the workings of the human mind and would serve well as a text in developmental psychology as well as for related courses in linguistics. The arguments are lucid and the subject matter is both fascinating and central to a more complete understating of language and the mind.

I have used this book, along with other similar sources, for writing a parametric grammar of Persian.The book is coherently organized into ten chapters: 1.Foundations Methods,Arguments,2.Government and Case, 3.Binding Theory,4.A-Movement,5.X'-Theory,6.A'-Movement,7.Barriers,8.LF Representation,9.Binding and Logical Form.10.Head Movement and Minimalism.Beginning with the second chapter the author picks up a syntactic problem and critically examines the solutions offered by linguists. For instance,in chapter four he concentrates on the analysis of the passive and its properties, namely, the movement of the underlying object into the surface subject position of the sentense in terms of a lexical analysis, a movement hypothesis and a chain relationship.Moreover, at the end of each chapter there are ample exercises from varius languages ( except Persian, of course) for readers / students to ponder over. Crucially,readers/students can familiarize themselves with current linguistic as well as syntactic issues and their proposed solutions. Nevertheless, the book suffers from a couple of drawbacks concerning the ultimate plausible solution for each problem and , more significantly, the definition of principles and parameters as a theoretical foundation / approach selected by the author,as the title suggests.I consider the latter a critical issue because there seems to be a fair degree of concensus among researchers concerning the principles which describe univerasl properties of grammatical operations or structures.However, differences of opinions arise regarding the parameters and the components of the language in which they have to be found. According to Chomsy, parameters are associated with the principles of Universal Grammar.Other linguists attribute them to the inflectional system of the language, the fuctional categories or lexical categories in general.From this book one cannot understand the author's position on the theory of parametrisation.

Since Chomsky established the GB model in the early 1980's, many introductory books have been published. Culicover's book came out by the end of the GB fashion when most people were attracted by Chomsky's new ideas of the minimalist program (MP). However, this book is not out of date at all, since Culicover illustrated the GB theory in a very critical way providing with quite a number of problems which cannot be solved at ease within the GB framework. All those problems are interesting issues that generative syntax has to manage. Though the author gave some suggestions, the issues remained open both to the GB framework and the MP followers. After reading this book, you may realize that the GB model is not as good as most people believe and that the burden of the MP will be heavier when it has to take over what left insolvable in the GB.

I have this book with me for years. I did implement a visual measurement system on PCB fault detection, with the algorithms (image operation and statistical measurement) given , I able to improved my first prototype. This book provided practical and workable case studies. It is a must for those would like to work practically on visual measurement system.

Modeling, Analysis, and Control of Dynamic Elastic Multi-Link Structure

Es una herramienta muy util en el calculo de los diferentes parametros thermo quimicos.

Tiene un presentacion amigable y facil de entender para el lector, locual lo hace un libro de consulta permanente para personas que trabajen en topicos afines.

This is merely a consensus of a limited number of people, many of whom do not practice and others with apparent private agendas. One of the supposed contributors was deceased long before it was even published. Makes me wonder how they even published it.... Pretty much a waste of time and paper.

This small group of 'experts' on chiropractic completely misrepresented the facts involved. They set out with an obvious purpose and this book is their attempt at a professiopnal takeover. A new guidelines book has recently been published and has been approved by the National Guideline Clearinghouse (a branch of US gov't). If this subject interests you, get the other one and save yourself some money.

The Mercy Center Guidelines reflect the highest standard of care in the chiropractic profession.