Young has done an admirable job at presenting some really beautiful and useful aspects of Hilbert spaces in a manner comprehendable for advanced undergraduates. After reading the book and reflecting on the experience, I'm somewhat amazed at the amount of nice ideas that were presented in such a compact text. The book cannot be compared with more rigorous and comprehensive texts such as Rudin, but you still get all the fundamentals of Hilbert space plus some wonderful applications.

I must strongly disagree with the reader from Sao Paolo who says that chapters 12 and 13 are poorly motivated. These chapters are crucial for the final theorem of the book in chapter 16. Parrott's Theorem in chapter 12 is the key to the foundational Nehari's theorem of chapter 15. Chapter 13 explores Hardy spaces which are the setting place for the major theorem of Adamyan, Arov, and Krein in chapter 16. In fact, I found the movement of ideas from chapter 12 to chapter 16 to be marvelously compelling. These chapters have extreme importance for theoretically oriented control engineers.

Only a modicum of real and complex analysis is necessary to understand the book. Knowledge of measure theory is not required.

This book is good to any control engineer who wants to know the background theory of optimization and robust control, but read read an analysis book first.

The first eleven chapters are an excellent introduction to functional analysis . Both Hilbert and Banach spaces are introduced carefully. Then there are two short chapters on orthogonal expansions and classical fourier series and then linear operators are studied. From the point of view of a person who is interested in applications to physics and engineering one can say that the book is well motivated mainly because is so compact and because of the many notes on applications. Chapters nine , ten and eleven on Green's functions and eigenfunctions expansions are extremely good. Chapters twelve and thirteen are poorly motivated from the point of view of applications.Finally chapters fourteen to sixteen try to exhibit the applications to complex analysis of operator theory and be helpfull to eletrical engineers.I think the book fails in this. So the ten first chapters of the book are excellent . The remaining less so

I used this book for a class last year. I found the organization quite horrible. There are 3 main multivariate models that he discusses in the book: Multiple regression, logistic regression and Cox proportional hazards. He ignores ANCOVA, ANOVA and multi-level frequency table (chi-square) methods.

Instead of writing about the 3 main multivariate models above individually he sporadically switches between all 3 models. The TOC is organized as a series of questions and answers. I would have preferred he wrote about each of the 3 topics separately.

Although finding the information you want is difficult, the book is written superbly. He makes it easy to understand difficult concepts such as interactions, model building, collinearity and testing of assumptions. You don't need a math background to understand this book. Aside from the organization of the contents, I loved this book! I would recommend for clinicians who are interested in learning about how multivariate models are created. If you review a lot of manuscripts in medical literature, this is a must read.

This is one of the best books I have ever read about biostatistics. It takes you further -from the usually well known table statistics to the model statistics using a step by step approach. Without covering the overall field, it tries to fortell readers' questions and answers them in the most explicit way. It's a book to understand what is going on around journals and makes your steps easier once you decide to try your way to dive in your numbers.

Straightforward approach to the concepts of multivariate analysis (MA) in medicine. If you don't know anything about MA and wanna understand it in a easy and fast way, this is the book. Katz also helps you to perform your own analysis. However, it's important to point out that a solid basis on statistical methods are needed for choosing the best method in a particular situation. The Cox model is not the solution for all problems!!! No strong math background is needed. This is a book of concepts and not of techniques. At least I can guarantee you'll understand the multivariate analysis published in NEJM and will find out about how common multivariate analyses are inappropriately used in medical journals. A big plus that every physician must read!

I only have the fifth edition of this book, but it is probably similar to this edition. I used this book, when I was teaching statistics many years ago. The book is very clear and it explains each statistical concept very thoroughly.

As an online statistics tutor, I find myself referring to it all the time. It has all of the topics that are normally covered in a first course in statistics. It also has some very good chapters on elective topics such as nonparametrics, sample surveys, and quality control. I took many courses in these subjects in undergraduate and graduate school, and I find that this book is a good review for some of the things I've forgotten.

I have many statistics books both elementary and advanced. This is one of only two elementary books that I would purchase again (my teacher's edition is losing the binding!).

It is probably the most complete book on statistics that I have ever read at this level. I would certainly recommend this book to anybody who is taking statistics for the first time. I would also recommend this book to statistics majors who plan to go into teaching and need a good review text.

This is a definately worthwhile learning tool which can aid anyone who is attempting to tackle statistics for the first time. The methods and theories are concise, direct, and most of all, clearly stated. The authors bring you step by step through each procedure and then offer exercises to demonstrate the process while giving you the confidence to go on.

This book was puchased midway through the semester. At that time I was struggling to maintain a C average. With the help of this book I was able to close the semester with an 89% average.

After taking this course for the second time, I found that this book really explained concepts well. I had trouble learning statistics the first time, but this book adds real-life applications making it easy to learn why it works the way it does. If you are hesitant or jittery about this class...relax. This book will make your life easier.

I used this book when I took OR class and I think that the book is quite good but it lack of theory calculation and also scientific calculation about each problem. In general I still believe that this is a good book.

I own both editions where I belive the 1st edition is better than their second. I don't particular like their new approach in teaching network modeling; it's non-intuitive. The first edition was a bit more 'logical' and easier to set up than the approach use in their 2nd edition. Secondly, their use of the Palisade @Risk is definitely a good choice, but the time lock (1 year if registered online) somewhat deflates the enthusiasm knowing that at some future date your software will cease to work. I bought the @129 upgrade but jumped through hoops with palisades (their authorization code did not undo the time lock and tech support argued that it was a publisher issue--in the long run they discovered a problem with the software where it was not taking the time lock off the application as designed.) I do like the 2nd edition's choice of larger fonts and the broader examples. I am still yet disappointed that unlike many other quality text books, the text does not include answers to 'odd' or even selected problems. I don't think the authors realize that their text is used by professionals looking to develop workplace skills and are not necessarily enrolled in a formal academic setting. Nevertheless, I bought the second edition because I think management science is a terribly valuable skill to have and that the authors have published the best book in the area of MS.

I am a business unit manager who frequently purchases books and software to maintain my level of competence in operations management, and I recently purchased the second edition of this book, copyright 2001. I have found it to be a great value, and agree with the reviewers the earlier edition who found it to be a very fine text on Operations Research. It comes with the standard version of Palisade's Decision Tools software, which is just outstanding. I wouldn't hesitate to recommend this book to anyone. Additionally, there's an option to upgrade to a fully licensed edition of this software at a greatly reduced price; the student version that comes with the book is fully functional, but is only licensed one year for students, 30 days for professionals. Microsoft doesn't give their software away for free either.

This book is too technical and has too much math. A better book for the elementary learner is "Practical Statistics: Simply Explained," by Russell Langley. Bulmer's book may be useful to me later on after I understand basic statistics. But don't waste your money if you know little about statistics and you don't like complex mathematical explanations.

This brief book gives an understandable introduction to the main ideas of statistics, with problems at the end of each chapter, and answers in the back. There is a bit of calculus. The book is nicely written, with interesting examples.

This modest little book is both a masterpiece and a gem! I can't praise it enough! It is different from any other statistics book I have ever read in that it puts you in the place of famous historical figures in statistics and helps you rediscover their findings. His use of original source material is very well done. The book is self-contained and the author proves almost everything of importance(some of the proofs are more intuitive than rigorous at times, but that's the point). Bulmer has a knack of making the most difficult concepts (hyperspace, degrees of freedom) seem natural. He covers a very broad terrain from distributions, tests of significance, inference, Bayesian methods, etc. Written on many levels, this is useful for a novice or intermediate student but I suspect professional statisticians will find much to keep them thinking about. While reading through this book you will often say "aha, so that's why they do that". For the price it is the best value possible; you won't regret picking up a copy of this book and if you enjoy the inner workings of statistical theory you will refer to it again and again.

This is the best introductory SAS book I have seen. It introduces the basic SAS structure and programming statements. A good and detailed explanation is provided for DATA step vs. PROC, a topic that always proves to be difficult to grasp for SAS newbies.

The book starts with SAS terminology and logic, i.e., how SAS works its magic. It moves on to simple tasks such as reading in data, summarizing it, and displaying it. Then there are chapters on SAS programming elements (expressions, logic flows, etc.) as well as intermediate-advanced statements. The MERGE statement is explained very clearly.

Examples abound, although I feel that they are presented in a very confusing format -- often you can't tell if a block of text belongs to the main text or an example. The organization of the book is also a little confusing, esp. if you want to use it as a reference book (not recommended; stick with SAS manual set instead).

In short, this book provides an excellent ovewview of SAS. Read the chapters in sequence and you'll soon be on your way to happy SAS'ing!

I went to the Fundamentals of SAS course held at the SAS Institute and was left in dire need of more information. This book was a first step. The exercises in the book were helpful and reinforcing. If you need more than brginner's knowledge, then you'll have to purchase another book but this is good to get started.

If you are in need of data management or analysis, SAS is likely big on your list. This book gives extremely clear and useful introductions to how SAS is structured, how to manipulate and organize data, and some basic statistical procedures (descriptive statistics, ANOVA, OLS models, etc.) are also presented.

Official SAS manuals are usually bulky, complicated, and difficult to understand, particularly if you have little/no experience with SAS. This book can take a complete beginner through data set creation and manipulation into substantially more complex and important procedures and functions. As this is an introduction to the SAS system, the more advanced functions in SAS, such as SAS STAT, are not covered in any detail. However, in order to understand how to actually use SAS and manipulate data so as to employ these higher level procedures, this book is excellent.

This is the absolute best introduction on how to use the SAS system I have seen, but it has lots of useful information for people with some basic SAS knowledge as well. It is presented in the style of a textbook,with each section concluding with problems (with answers provided) that the aspiring SAS programmer can solve.

If you are just starting to look into SAS, I cannot recommend this book highly enough. 'If I was able to do it, anyone can.'

This book is excellent if you already know why you want to know the material in it. Then it is concise, to the point, and very well-written. I turn back to it over and over again; my copy is very worn by now.

When I first started reading it, I was not too pleased with it. As a text-book it suffers from not motivating the theory, and not connecting it with parallel approaches. The subtitle mentions applications. Now, what one person considers applications is what the next person considers abstractions. My point of view is truly applied - I want to use SDE's to model real-world phenomena (actually, not financial ones) and are less interested in SDE's per se. So I would have liked more connections with physics (for instance advection-diffusion transport phenomena) and I would have liked the material to be more solidly anchored in general stochastic processes. Nevertheless, I appreciate that the book wouldn't have been as concise, then.

As a so-called practicising 'quant' in a top Wall Street Investment bank, I came upon this book from colleagues who raved about the exposition of the material found in this book.Indeed even though I have an engineering and advanced mathematical background, I find the material to be useful in helping to understand the more research oriented finance journals. From a practitioner's view point the most fundamental aspect of the book is the statement where it states the solutions of SDE's can be thought of as inherent Browian motions for it is the latter which enables one to price the financial instruments one commonly hears of in the press.I would recomend first understanding the physical and mathematical aspects of Browninan motion before tackling the abstract field of stochastic calculus so that meaningful interpretations can be drawn.Nevertheless the book gives excellent penetrating coverage of what SDE's are.For budding so-called 'rocket-scientists' who want to make mega-bucks on the markets, my advice would be to first master partial differential equations (because this is the only way to pragmatically price things like exotic derivatives) then for their own enlightenment they can read this book if only just to keep up with the jones's.

This a perfectly written book on stochastic calculus, especially needed for junior (but rising!) financial quants. All themes are carried out with a profound pedagogical talent. For a practitioner, the book loses nothing to Karatsas and Shreve, but is a much shorter, simpler and joyable reading. Yet, it is a systematic text book that covers most classical results with (important!) accessible proofs. For example, the Kolmogorov equations (forward and backward) are derived, not just stated as in most other texts, Girsanov's theorem is relatively well covered (although the author has not demonstrated its computational side well enough, but this is a common disease). Ideas are illustrated by practical problems (including those from quantitative finance). What I also liked, Oksendal's SDE theory is much closer to "differential equations", than what is often presented by probabilists. A must for every practitioner who works with stochatic processes.

While Boyle dishes up some fascinating mini-biographies, and some solid (if sometimes poorly-organized and repetitive) examples of how, when we measure too much, we measure nothing completely and little of that well, the book falls apart toward the end, as we get to hear about how civilization will be saved if only we ... measure different things than what we're already measuring. The closer this book comes to the present, the more dated it feels.

After 7 years in the actuarial profession and before beginning to pursue my Ph.d in Mathematics, I decided to read this book. After my experience in corporate america, I hoped that a critical evaluation by an expert might resolve some of the conceptual "difficulties" that I encountered while still a productive member of society as measured by GNP and not a net-capital-zero, ivory-tower academic. Anyway, I was not disappointed.

This book starts slowly, but is well-structured. The background provided on Bentham/Malthus/Mills is sometimes tedious and occasionally superfluous, but mostly necessary and builds the foundational context to appreciate fully ideas presented later in the book. I think that the author includes personal details that paint a POSSIBLY unjustified mechanistic, and thus, inhuman, aspect into the personalities discussed and therefore their theory (utilitarianism). But, maybe the emphasis is necessary to accurately capture the personalities involved. Anyway, the author gets an 8 for objectivity. In my opinion, there's gotta be some polemic content for it to be interesting, otherwise you just have a textbook. He strikes a good balance.

The first half of the book discussed above answers the question "Where did all this [stuff] come from?". The latter half of the book concerns itself mainly with "How did it all come about?". Keynes and his ideas in suitable context is developed here and I personally found the content regarding him to be fascinating. He is now a permanent addition to my previously blank list of responses to the "who would you wanna have dinner with?" question. I never realized how distorted and abused his conception has become.

The remainder of the book brings us up to date and I learned a thing or two. Now, I'm going to put the most important part at the end. In order to enjoy this book at all, you have to accept one of the following two hypothesis:

(1) It is government's role to be concerned with the "general welfare" of the populace

or

(2) Government is going to be concerned with same regardless so at least it ought to make some sort of sense granting the false assumption (1). Whatever the heck that means. In other words, suspend reality and try to find some enjoyment in the simplistic and misguided attempts to get around the problems created by that same false assumption.

It was a good read and thought-provoking, I'm not going to spoil it anymore. I'd give it a 4.3 stars if possible, but they have us restrained to integers. Ha-ha-ha!

I struggled to find this book under the alternative title 'The Tyranny of Numbers' of the HarperCollins edition that I read. But it was too good not to review.

OK, from a mathematician's point of view there is no proof here that numbers and counting will never make us happy. But the sequence of efforts described by Mr Boyle - from Jeremy Bentham to David Pearce - have all met the same fate. A definite improvement in our understanding of ourselves and our social condition (although not without serious misrepresentation too). But, in the end, there is always the realisation that the initial objectives - so powerfully believed in - are not achieved, that the shortcomings in each method of analysis leave us crying out for just another try. Will we ever tire of trying? Will we just give up and move on to other human endeavours?

As I read this book, and met historic characters I probably hadn't given a thought to since I did High School British History, I couldn't help thinking that there is another book to be written. 'The Tyranny of Bits: Why computers can't make us happy'. For all their achievements computers, like the tools of analysis described by Mr Boyle, can't help exposing their own shortcomings. But does the world - especially the politicians - know this yet? Computer output is so seductive - we desparately would like to have some sort of tool that will take away - reliably - some of our own fallible judgement that we so often have to rely on. As Mr Boyle shows it is not numbers that can do this - I suspect its not computers either.

ERRATA

Page 7, beneath Eqn 2-1, this statement is completely erroneous and needs to be removed: "Note that Avg and ..."

Page 85, next to last paragraph, replace P=Avg with P-Avg.

John T. Thorngren

Powerful- a real sword to all those who believe in the tooth fairy

An excellent book that mathematically exposes "hot number", wheeling, and other "gimmicks" sold as sure fire methods to win the lottery -

I work with 5th and 6th graders, who can not sit still for abook read their grade level--not even Harry Potter. Because this book introduces the concept of a fairly sophisticated vocabulary word, "serendipity", it was a hit with the 11 and 12 year olds. They were able to learn from the book's delightful examples what serendiptiy means. Because the text per page is short, they could listen, even those students whose attention spans are not long. A welcome book for most collections. Highly recommended.

Our family truly loved this book, and immediately recognised the delightful style of illustrator, Peter Reynolds! Reading this made me go back 40 years, and recall my own "serendipitiest" moment... that of riding my first two-wheeler, with my dad running along beside me, and holding the back of the bike for balance... sailing down the street, glancing back..... with the realization that my dad had let go WAY back at the beginning of the ride! This story will bring a serendipity moment to all who read it. We've all had them! Thanks Toby and Peter for reminding us!

This is an amazing book. It has quickly taken its place as one of my daughter's favorites (she particularly likes to say "serendipity"!). I would thoroughly recommend this book to any parent who is looking for that rare children's book that is as enjoyable to read aloud as it is for a child to hear.