Scientific Computing

Book Description

Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems.

Customer Reviews:

very nice conceptual overview.......2006-07-22

Wow, people seem to be really split on this book. I had Mike Heath for numerical analysis/scientific computing and he was an excellent instructor, one of the best lecturers I've ever had. (As a consequence, I have a hard time separating the book and the class, so judge accordingly.) The book is based on his lecture notes, though he added some material and didn't cover every topic in the book. Just reading the book is useful to give you an overview of the point behind different methods. The goal of the class for which this book was written is actually quite conceptual. It was to give scientists (that's me: a stats researcher who makes heavy use of numerical computation) and CS people in areas other than scientific computing a leg up. It was only a first class for people in scientific computing, the rough equivalent of intro Physics or intro Probability/Stats for people in those respective majors. However, you *won't* be prepared to "roll your own" from this book. In fact, at the beginning of the semester Heath was very careful to note that if you have the opportunity to use a library function for most numerical programming, you are nuts to roll your own. Why? Numerical algorithms are usually extremely complicated and the authors of the code often spend years developing careful expertise on them. Frequently the formulas used to elucidate a given method are NOT the ones used to implement it. You need error traps, tricks to handle ill-scaling and other special cases, etc. These are things that someone who has a one-semester, superficial understanding of a topic simply won't have. So consider the book on the goals it set: it is an overview of a field. If you want to learn more about any one topic, you have to dig deeper and consult references and other works, but this is a good place to start. For this, the book serves admirably.

Not for the practitioner.......2005-11-17

If you are interested in Scientific computing from the viewpoint of the end user that is the guy who uses the method to solve practical engineering problems then this book is lacking.

Not enough methods in this book to constitute an introductory survey of the field. Every chapter gets heavy dose mathematical treatment, apparently Heath loves his math but for the rest of us it doesnt translate into know-how. Know how to solve equations using computational techniques. Very few derivations to back his mathematical swagger, very few examples (if any) and fewer numerical schemes to solve problems. Many of the chapters receive cursory treatment such as PDE's get about 70 pages of print. Far too little to do anyone any good.

He does talk about interesting issues such as conditioning and error analysis and computer precision and memory issues but it is done from such a superficial viewpoint that one cannot use anything to improve ones code. Not recommended if you want to learn numerical methods even if you have an excellent professor to learn from. His chapter on FFT's was even more abstruse and there was hardly any methods with which to solve PDE's.

I had this for a graduate course in Numerical Methods but ended up using Hoffman's excellent book on Numerical Methods.

Trash.......2005-10-14

If you want to have a solid understanding of numerical computation, this book is definitely the last choice. Many theorems are given without any proof or even intuitions behind them in this book. Even when a proof is provided, it's often far from rigorous. The organization of chapters is the worst I have ever seen, revelant materials are scattered over several different locations rather than put together. Take the SVD for example, it is mentioned in the end of chapter 3, but reappears in chapter 4, which is very confusing. If you are new to this area, please don't read this book. It gives you many many facts without explanations, which I think is not a good way to learn new things. David S. Watkins' Fundamentals of Matrix Computations is a lot better and easier to understand. It also emcompasses many detailed treatments of various theorems. If you have bought Heath's book, don't be sad, at least it can serve as a coaster.

Excellent Introduction, Sparse on Details.......2004-11-20

While sparse on the details of many of the algorithms and theorems mentioned, as an introduction it covers a broad range of material-enough for two semesters of study. The writing is lucid, and when a proof of a theorem is given, it is easy to follow and explained in english afterward. Rationale is given for everything, which is a great benefit to a student not familiar with the nuances of sophisticated linear algebra.

A Good Introductory Survey.......2002-11-05

This book excels at presenting a reader with little to no knowledge in computer science and a mild mathematical background (knowledge of differential equations as a prerequisite) with the fundamental concepts regarding scientific computing. The presentation of pseudo-code algorithms helps smooth the transition from analytical (pencil and paper) thinking to numerical thinking. The algorithms are presented in a manner such tha anyone with access to dozens of possible environments can apply them, though they are by no means complete, thus requiring some thought into the processes. The material covered is 110% of what an engineer will want to know, 90% of what an applied mathematician will want to know, and 45% of what a numerical analyist will want to know. In all, a great book to begin a foray into numerical computing.

Applied Statistics For Engineers and Scientists Using Microsoft Excel and MINITAB (With CD-ROM)

Average customer rating:

Very Practical Book
Good for first edition

Applied Statistics For Engineers and Scientists Using Microsoft Excel and MINITAB (With CD-ROM)
David M. Levine , Patricia P. Ramsey , and Robert K. Smidt
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

Statistics | Economics | Business & Investing | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Business & Investing | Qualifying Textbooks - Fall 2007 | Stores | Books

Computers & Internet | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books

Look Inside Business Books | Trip | Specialty Stores | Books

Look Inside Computer Books | Trip | Specialty Stores | Books

Look Inside Nonfiction Books | Trip | Specialty Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books
Similar Items:

ASIN: 0134888014

Book Description

This applied book for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software complete this treatment of statistics. Chapter topics include describing and summarizing data; probability and discrete probability distributions; continuous probability distributions and sampling distributions; process control charts; estimation procedures; hypothesis testing; the design of experiments; and simple linear and multiple regression models. For individuals interested in learning statistics—without a high level of mathematical sophistication.

Customer Reviews:

Very Practical Book.......2003-11-30

I have found this book to be very useful with practical examples and case studies. I felt that as an engineer I needed to know how to use software(to save time)along with the formulas that work in it.This book satisfies that, using a very common software EXCEL..what could be better than this.
I strongly recommend this book for a high level course in statistics.

Good for first edition.......2002-05-10

I used this textbook for a course in statistics. I must say that it was better then the first time that I had taken statistics 5 years ago. The book uses one or two data sets per chapter that helps you focus your thoughts while learning the different techniques. A nice feature about this book that wasnt available 5 years ago is the Excel and Minitab examples which saves a lot of time that is ordinarly spent on copious number crunching. I would have given the book 5 stars, however I found some obvious errors in the book that should have been edited out before the release. Good starter book for sats.

Applied Statistics and Probability for Engineers

Average customer rating:

A Very Good Applied Stat Book
Not recommended for self study
Not that good
Applied Statisitics and Probability for Engineers
Best engineering text on statistics

Applied Statistics and Probability for Engineers
Douglas C. Montgomery , and George C. Runger
Manufacturer: Wiley
ProductGroup: Book
Binding: Hardcover

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

General | Arts & Photography | Subjects | Books

Look Inside Art Books | Trip | Specialty Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Arts & Photography | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Accessories:

Excel for Engineers and Scientists, Second Edition

ASIN: 0471745898

Book Description

Real Engineering Situations, Real Engineering Data

With Montgomery and Runger's best-selling engineering statistics text, you can learn how to apply statistics to real engineering situations. The text shows you how to use statistical methods to design and develop new products, and new manufacturing systems and processes. You'll gain a better understanding of how these methods are used in everyday work, and get a taste of practical engineering experience through real-world, engineering-based examples and exercises.

Now revised, this Fourth Edition of Applied Statistics and Probability for Engineers features many new homework exercises, including a greater variation of problems and more computer problems.

Key Features
* The text treats all topics in a way that reflects today's engineering realities. In the probability chapters, the authors emphasize engineering-specific examples, rather than counting methods or artificial applications such as gambling.
* Examples and exercises throughout the text use real data and real engineering situations.
* Coverage of probability is lively and interesting. It is complete but concise so as not to take over the content of the entire text.
* Thorough coverage of regression modeling, design of engineering experiments, and statistical process control from experts in these topics makes the book especially useful as a reference.

Customer Reviews:

A Very Good Applied Stat Book.......2007-09-25

The book is very good for applied Statistics in engineering. It has many practical engineering examples that an engineer can apply at work. The "FREE Access to Online Student Resources Inside" white envelop interferes with opening the first few pages of the book when it is brand new. The book is well written.

Not recommended for self study.......2007-06-09

This book is not recommended for self study or distance courses. There are only sporadic answers to odd problems, most books of this type have answers for every odd problem. The student solution manual is even more worthless, some chapters have only 2 or 3 worked problems per chapter. Learning statistics with this book in a distance education course is really more painful than it should be. If you have to get this book, do not waste your money on the student solution manual.
This book may be a good reference to someone who already knows statistics, but to someone learning, especially without the benefit of lectures, the description and examples are way too sparse.

Not that good.......2007-05-12

The answers it gives you are sporadic and some are hard to follow. I was expecting solutions to all the odd problems and a little more detail with the solutions. I would not recommend buying this unless it were $10 or less.

Applied Statisitics and Probability for Engineers.......2006-11-05

Very comprehensive text, would be an excellent undergraduate text or
postgraduate reference. Must have book for Statistics and Probability.

Best engineering text on statistics.......2006-02-12

The third edition has been improved but has the same practical feel as earlier editions. Real data is used for most examples and having the "entire book" on a CDROM including the data sets, solution manual and supplimental material puts this text "over the top" in terms of usefulness. It is an excellent reference for the practical engineer who uses statistics only occasionally.

I use this in industry and teach internal (to the company) courses using this text. The CDROM really makes it the text of choice.

Applied Survival Analysis: Regression Modeling of Time to Event Data

Average customer rating:

A Good Read, but Read it Carefully!
nice introduction
Great conceptual Introduction to Cox regression analysis
A clear, simple introduction to survival models
Excellent Nontechnical Coverage of Survival Analysis

Applied Survival Analysis: Regression Modeling of Time to Event Data
David W. Hosmer Jr. , and Stanley Lemeshow
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

General | Mathematics | Science | Subjects | Books

General | Medicine | Subjects | Books

Biostatistics | Research | Medicine | Subjects | Books

General | Research | Medicine | Subjects | Books

Research | Medical | Professional & Technical | Subjects | Books

Biostatistics & Epidemiology | Medicine | New & Used Textbooks | Stores | Books

General | Medicine | New & Used Textbooks | Stores | Books

Nursing | Medicine | New & Used Textbooks | Stores | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Computers & Internet | Qualifying Textbooks - Fall 2007 | Stores | Books

Medicine | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books
Similar Items:

Accessories:

Solutions Manual to Accompany Applied Survival Analysis: Regression Modeling of Time to Event Data

ASIN: 0471154105

Book Description

A Practical, Up-To-Date Guide To Modern Methods In The Analysis Of Time To Event Data.
The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health-related researchers who study time to event data. This book helps bridge this important gap in the literature.
Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail. Key topics covered in depth include:
* Variable selection.
* Identification of the scale of continuous covariates.
* The role of interactions in the model.
* Interpretation of a fitted model.
* Assessment of fit and model assumptions.
* Regression diagnostics.
* Recurrent event models, frailty models, and additive models.
* Commercially available statistical software and getting the most out of it.
Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields.

Customer Reviews:

A Good Read, but Read it Carefully!.......2005-05-05

The authors provide a really nice, non-technical survey of the landscape for Cox Proportional Hazards models. A nice aspect of their treatment is the care they take to reference all highly technical texts and journal articles. For example, if you'd like to find out more about goodness-of-fit tests for survival models, the authors provide ample references to the Counting Process Theory of Martingale Residuals.

The first chapter discusses the basic characteristics of survival data, including the notion of censoring (in all of its various forms). Examples of the principle types of censoring are included. The chapter also includes introductory material on the general survival model, including a nice description of the log likelihood function. Curiously, the rigorous definition of the hazard function has been omitted, probably to avoid intimidating readers who are not familiar with formal limits.

Chapter 2 continues to build up the general survival model and introduces the relationship between the survivor function and the cumulative hazard. Pointwise estimators for the survivor function are discussed, including the Kaplan-Meier estimator along with the various variance estimators. Test statistics for comparing two survival populations are introduced, including the Log-Rank and General Wilcoxon statistics. The reader is encouraged to read the counting process treatments of these statistics to see why they produced defensible hypothesis tests.

Chapter 3 is devoted to the Cox Model and Cox's partial likelihood function. Tests for significance of the coefficients are introduced, included the Wald test, log likelihood ratio test and the score test. These are used heavily in the later chapters as the basis of a model-building methodology.

Chapter 4 is a very short, but nicely written chapter explaining how to interpret the values of each regression coefficent. It also describes covariate-adjustment techniques for model diagnostics.

Chapter 5 is just a wonderful chapter which outlines classical model building techniques. This is a great chapter for anyone who has ever been thrown a ton of data (with a bushel of possible covariates) and asked to "fit a model to this stuff".
Readers who have done a lot of purposeful fitting of linear regression models won't find the basic techniques new, but use of survival specific residuals and selection criterion will probably be an eye-opener. The section on assessing the functional form for continuous covariates is also nicely written.
However, the section on Best Subsets Selection was a little too "cook-booky" for my taste.

Chapter 6 is another very nice chapter on goodness-of-fit. It discusses analysis of the various residuals and their use for analysis outliers, testing proportional hazards assumptions and overall Goodness-of-Fit.

Chapter 7 discusses the standard extensions of the Cox model, including stratification and time-varying covariates. Chapter 8 discusses parametric survival models, and is a good introduction to the SAS procedure LIFEREG. The generalization of the Cox model to recurring event data (also know as Aalen's multiplicative intensity model) can be found in Chapter 9.

My only complaint is that each chapter was designed to be read in one sitting. Individual ideas, topics and formulas can be buried in a seemingly unbroken chain of paragraphs. The lack of sub-sub section titles,etc, makes using the text as is somewhat cumbersome to use as a desk reference. I've gotten around this limitation by marking key concepts, etc., in the margin in order to give a "quick search" capability enhancement to the index.

nice introduction.......2003-04-03

This book provides a good, clear, concise explanation of Cox's proportional hazards models. For someone seeking a non-mathematical description this is a great guide. The original datasets from the text examples can even be downloaded and you can go through the same process yourself. Because of some mistakes in the text, I would recomend looking at other sources as well.

Great conceptual Introduction to Cox regression analysis.......2000-02-09

I enjoyed the authors' book on logistic regression analysis in 1989, and this book is just as good, or better, with many extremely practical suggestions on building regression models for survival data. Happily, the authors summarize, compare, and contrast several major texts on survival analysis which have appeared in the past 10 years. For example, they discuss different names used by different authors for score residuals. They present a helpful appendix on the counting process approach to survival analysis, which will make more advanced texts accessible to students; thus, anyone who wants to use survival analysis, at any level, should consult this book, even if he has already studied books by Miller, Lee, Collett, Fleming-Harington,Andersen, et al, etc. An unfortunate drawback to this book is that the first printing contains many careless errors, some of which may affect student learning: for example, the definition of a survival function is misstated. I recommend that you insist on the second or third printing when buying this book, and you will be quite satisfied.

A clear, simple introduction to survival models.......2000-01-07

Hosmer and Lemeshow have given us a clear, nontechnical introduction to using survival models. The book strikes a good balance between covering the basics and addressing the most recent, state-of-the-art techniques, including repeated events, frailty models, and others. They also do a good job of addressing practical issues, including estimation details and available software. While most of the examples are drawn from medicine and biostatistics, this book could also serve as a useful starting point for social and behavioral scientists interesting in learning the fundamentals of these models, as well as a useful reference for applied researchers.

Excellent Nontechnical Coverage of Survival Analysis.......1999-12-07

Applied Survival Analysis is an excellent book for someone seeking a non-mathematicial explanation of survival analysis. The book covers the motivation behind the development of survival analysis, estimation of survival curves, the Cox proportionial hazards, and some parametric models. The book also covers the major methods used in variable selection, model building, and diagnostics. Someone with an undergraduate background in statistics and econometrics will understand the book. The book relies on text to discuss the methods and uses mathematical formulas only when absolutely necessary. Numerous examples are used to highlight what the text covers. The math that is used is easily understandable. This book is ideal for someone who needs to learn the tools of survival analysis but not how they were derived.

Applied Statistics for Engineers and Scientists (with CD-ROM)

Average customer rating:

Be careful, numerous errors
Excellent statistic tool
A Great Book for Engineers

Applied Statistics for Engineers and Scientists (with CD-ROM)
Jay L. Devore , and Nicholas R. Farnum
Manufacturer: Duxbury Press
ProductGroup: Book
Binding: Hardcover

General | Engineering | Professional & Technical | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

Look Inside Science Books | Trip | Specialty Stores | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

ASIN: 0534467199

Book Description

This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS emphasizes application of methods to real problems, with real examples throughout.

Customer Reviews:

Be careful, numerous errors.......2007-04-26

This book is full of errors. Not only in the text, but our class found that numerous answers to the odd problems (in the back of the book) were wrong. It became so bad that when your answer differed from the book's, your first instinct was to assume that your answer was right and the book's answer was wrong. (Not a good thing in a text book). And, since the book was published in 2005, one would think that the publisher would have made an errata available on their web site. My suggestion would be to look elsewhere for a better book.

Excellent statistic tool.......2007-03-17

Nice package of useful stat information, in a small and handy format. I'll hang onto this.

A Great Book for Engineers.......2003-06-25

This book is very good for engineering and business. The book is easy to read and to follow. I apply statistics concepts from this book in business and technical problem solving at work. This book has 11 chapters. These chapters have statistical techniques that the industry is using. The student solution manual is also a great tool to learn statistical techniques from this book. It is great!

Average customer rating:

Tremendous Work and Very Clear
Correction to the quotation from JEI
Extremely thorough and rigorous resource
Very good and the most complete of the field!

Foundations of Image Science
Harrison H. Barrett , and Kyle Myers
Manufacturer: Wiley-Interscience
ProductGroup: Book
Binding: Hardcover

General | Engineering | Professional & Technical | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

General | Physics | Science | Subjects | Books

Molecular Physics | Physics | Science | Subjects | Books

Optics | Physics | Science | Subjects | Books

General | Arts & Photography | Subjects | Books

All Deals | Blowout Books | Stores | Books

Arts & Photography | Blowout Books | Stores | Books

Science | Blowout Books | Stores | Books

All Amazon Upgrade | Amazon Upgrade | Stores | Books

Arts & Photography | Amazon Upgrade | Stores | Books

Engineering | Amazon Upgrade | Stores | Books

Medicine | Amazon Upgrade | Stores | Books

Professional & Technical | Amazon Upgrade | Stores | Books

Science | Amazon Upgrade | Stores | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Arts & Photography | Qualifying Textbooks - Fall 2007 | Stores | Books

Medicine | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books

Look Inside Art Books | Trip | Specialty Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books
Similar Items:

Introduction to Fourier Optics
Computed Tomography: Principles, Design, Artifacts, and Recent Advances (SPIE Press Monograph Vol. PM114)
Principles of Nuclear Magnetic Resonance Microscopy
$Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (7th Edition)$ Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (7th Edition)
Fourier Transform and Its Applications

ASIN: 0471153001

Book Description

Winner of the 2006 Joseph W. Goodman Book Writing Award!

A comprehensive treatment of the principles, mathematics, and statistics of image science

In today’s visually oriented society, images play an important role in conveying messages. From seismic imaging to satellite images to medical images, our modern society would be lost without images to enhance our understanding of our health, our culture, and our world.

Foundations of Image Science presents a comprehensive treatment of the principles, mathematics, and statistics needed to understand and evaluate imaging systems. The book is the first to provide a thorough treatment of the continuous-to-discrete, or CD, model of digital imaging. Foundations of Image Science emphasizes the need for meaningful, objective assessment of image quality and presents the necessary tools for this purpose. Approaching the subject within a well-defined theoretical and physical context, this landmark text presents the mathematical underpinnings of image science at a level that is accessible to graduate students and practitioners working with imaging systems, as well as well-motivated undergraduate students.

Destined to become a standard text in the field, Foundations of Image Science covers:

Mathematical Foundations: Examines the essential mathematical foundations of image science

Image Formation–Models and Mechanisms: Presents a comprehensive and unified treatment of the mathematical and statistical principles of imaging, with an emphasis on digital imaging systems and the use of SVD methods

Image Quality: Provides a systematic exposition of the methodology for objective or task-based assessment of image quality

Applications: Presents detailed case studies of specific direct and indirect imaging systems and provides examples of how to apply the various mathematical tools covered in the book

Appendices: Covers the prerequisite material necessary for understanding the material in the main text, including matrix algebra, complex variables, and the basics of probability theory

Customer Reviews:

Tremendous Work and Very Clear.......2006-11-29

This is one of the few books that I will always treasure. Why? Because it is very clear. It has very very good discussions on everything it treats, and it treats a ton of material. In my engineering career, I have read or tried to read many many textbooks and this stands up as one of the absolute best. Barrett and Meyers give exquisite expositions on all of the mathematics necessary to study image science and many other related fields. For example, its treatment on probability, random processes, decision and estimation theory is actually better, more clear and more complete than many standard textbooks on the subject. If I get stuck reading any of them, I refer to this book and am saved.
I only wish they would issue it in two or three volumes. It is so ponderous (yet beautifully put together) if you carry it around you will get big muscles and get a good cardio workout!
I own it and leave it at home and I had the library at work get me a copy which I leave at work. If I want exercise I will go to my health club!
IT IS WORTH EVERY PENNY OF THE 146 BUCKS IT COSTS.
If you want a great textbook to learn this technology from dont hesitate to buy it. You may need two - one for home and one for work, if your company wont buy you one.
Really impressed.

Correction to the quotation from JEI.......2006-08-20

I was the reviewer for this book in the Journal of Electronic Imaging.

The quotation from my review in JEI as it appears on this site should read:

"...a worthwhile addition to the armamentarium of any serious researcher in image science and will be an oft-quoted reference for many years to come." (Journal of Electronic Imaging, April-June 2005)

The corrections pertains to the word, oft-quoted, which has, for some reason, appeared as "opt-quoted" on this site in addition to the reference, "Journal of Electronic Imaging" instead of "Journal of Electrical Imaging"

This book, of course, is outstanding as I have stated in my review in the JEI.

Extremely thorough and rigorous resource.......2006-02-10

This book always amazes me whenever I use it for the absolutely incredible amount of material that it covers in such depth. I had the tremendous good fortune to have taken a Physical Optics course with Prof. Barrett, and it would be impossible to believe that one person can know so much unless you have personally talked with him about science or had a class with him. The rumor in the department is that Dr. Barrett is the only professor to at one time or other have taught ALL of the department's core graduate courses during his career at the College of Optical Sciences. Furthermore, he is one of the rare scientists who is an authority in his field both theoretically and experimentally, so you do not get a one-sided perspective as can often happen with science texts. The book reflects his vast knowledge, expertise, rigor, and thoroughness.

Of course, the book has several chapters on mathematical formalism, including the linear algebra, dirac delta function, Fourier theory, and group theory. The imaging theory is there, as well as diffraction theory. He covers photon statistics and detection, including the necessary quantum mechanics. He covers several advanced imaging concepts that I haven't any idea about myself. You probably could not find a more comprehensive book in the field of imaging and physical optics. Another benefit is that, at least for the chapters I have used, the individual chapters seem to stand well on their own and you are not forced to study the book in order.

This book is not for the faint of heart in any respect. The material itself is not for the faint of heart: it is extremely rigorous and will require your careful attention, but I believe it is well explained and manageable for someone who is serious about learning it. The size of the book is not for the faint of heart. I would hate to have to carry this thing around much (>1500 pages!!). The price is nothing to sneeze at either, at least for an impoverished graduate student like me, but Dr. Barrett told us that if you calculate the cost per equation, it may be one of the cheapest books on the market. Well, you get what you pay for. As far as anyone in the class found out, there are no typos, either. (Really. We were looking for them). This is certainly a relief for anyone who has much experience shelling out hundreds of dollars for expensive science textbooks.

I do not consider this book to be introductory material, but it is quite likely as close to exhaustive as anything you are apt to encounter in the physical sciences. If you are very serious about imaging or physical optics, this book will be an invaluable resource.

Very good and the most complete of the field!.......2004-02-18

The authors have done a great work. The book is complete and detailed. It is helping me a lot in the beginning of my Ph.D. It's really a must have in the field!

Probability and Statistics for Engineers and Scientists (7th Edition)

Average customer rating:

A decent undergrad book on the subject
It is ok, but ...
Rough, Very Rough....
Engineering Specialist
The 6th Edition is among the best I've seen...

Probability and Statistics for Engineers and Scientists (7th Edition)
Ronald E. Walpole , Raymond H. Myers , Sharon L. Myers , Keying Ye , and Keying Yee
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

General | Engineering | Professional & Technical | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

General | Engineering | New & Used Textbooks | Stores | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

ASIN: 0130415294

Book Description

This classic book provides a rigorous introduction to basic probability theory and statistical inference that is motivated by interesting, relevant applications. It assumes readers have a background in calculus, and offers a unique balance of theory and methodology. Chapter topics cover an introduction to statistics and data analysis, probability, random variables and probability distributions, mathematical expectation, some discrete probability distributions, some continuous probability distributions, functions of random variables, fundamental sampling distributions and data descriptions, one- and two-sample estimation problems, one- and two-sample tests of hypotheses, simple linear regression and correlation, multiple linear regression and certain nonlinear regression models, one factor experiments: general, factorial experiments (two or more factors), 2 k factorial experiments and fractions, nonparametric statistics, and statistical quality control. For individuals trying to apply statistical concepts to real-life, and analyze and interpret data.

Customer Reviews:

A decent undergrad book on the subject.......2007-08-20

This is one of the better undergrad-level books on the subject, and the fact that it's now in it's 7th edition (as of this writing) shows that it's still in use in the halls of academia. My copy, if I remember correctly, is either a first or second edition.

Unfortunately for me, I had a sub-par instructor (and a different text book) the first time I studied the material, and even though I got high marks in the class, I re-audited the class again, on my own time, with a different instructor, the following semester. The different instructor, and text book (this one), made a big difference, and really helped bring the material to life for me ... even though it cost me half of a perfectly good summer vacation to do it.

Let's face it ... probability computations, permutations, and confidence intervals, can be a bit dry (and a hot classroom with no air conditioning didn't help matters), but Wadpole does a decent job of not only covering the material well. There are plenty of worse books on the material out there, trust me. This one's better than others I've seen.

It is ok, but ..........2007-02-02

This is an OK book but too expensive for what it is. I learned a lot from the book. The excercises are good but the wording is sometimes confusing. You have the answers for "odd" exercises in the back of the book, but it looks like that the authors added new exercises in this edition and the answers are in the back of the book, therefore, you don't know if you got the right answer.
You better read some other Basic Statistic book, before you using this book. Good for people that study Science or Engineering.

Rough, Very Rough...........2006-11-25

The problem with this book is that it can not decide whether it is a proper mathematics book, spending time on formal proofs and on mathematical intuition, or a "recipes" book simply providing the reader with a list of statistical techniques.

The author spends some time going though the sequential building blocks of statistical theory, presenting key theorems, but only to leave more than 1/2 of them as "exercises". This leads to a number of problems such as:

1) Uncertainty regarding the applicability of techniques without a proper derivation from first principles
2) The need to constantly fall back to detailed wording of past Theorems and Corrolaries to compensate lack of intuitive understanding
3) The inability of the author to differentiate between BIG ideas and little details (and the links between them...)

The book is therefore an OK framework to get a quick overview of the topic, for quick browsing and quick fixes, but in order to really cover the material properly, one needs to constantly refer back to more thorough and formal works.

Remember the Calculus books that try to compensate a sharp presentation of ideas and concepts by encyclopedic integration techniques ???

Engineering Specialist.......2006-03-25

With an exception of Chapter 1, this book is well written, well organized with logical flow of subjects, and having practical example for every chapter's sub-topics. I found most of these examples are simple and very supportive for the understanding of mathematical expressions and that link the underline subject with real-world application. This book, in my opinion, is an excellent text for science and engineering students as well as for scientist or professional engineer who wants to achieve his or her self-study of the fundamentals of probability and statistics.

If Chapter 1 had provided a right level of abstract for an introduction of book's chapters and eliminated trivial / obvious errors (e.g. on pp. 9 and 10) in this chapter then, I believe, the reader's impression of the book would increase significantly.

The 6th Edition is among the best I've seen..........2006-02-08

I don't have the 7th Edition, but the 6th Edition is helping greatly. The explanation of concepts are crystal clear and the examples make sense, are well explained.

Probability and Random Processes with Applications to Signal Processing (3rd Edition)

Average customer rating:

Good book for learning prob and stochastics for EEs
Wow...
Some good some bad
Great random processes book for engineers
Well written but lacks editing, a bit sloppy

Probability and Random Processes with Applications to Signal Processing (3rd Edition)
John W. Woods , and Henry Stark
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

Electrical & Electronics | Engineering | New & Used Textbooks | Stores | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books

Look Inside Science Books | Trip | Specialty Stores | Books
Similar Items:

ASIN: 0130200719

Book Description

Provides users with an accessible, yet mathematically solid, treatment of probability and random processes. Many computer examples integrated throughout, including random process examples in MATLAB. Includes expanded discussions of fundamental principles, especially basic probability. Includes new problems which deal with applications of basic theory—in such areas as medical imaging, percolation theory in fractals, and generation of random numbers. Several new topics include Failure rates, the Chernoff bound, interval estimation and the Student t-distribution, and power spectral density estimation. Functions of Random Variables is included as a separate chapter. Mean square convergence and introduction of Martingales is covered in the latter half of the book. Provides electrical and computer engineers with a solid treatment of probability and random processes.

Customer Reviews:

Good book for learning prob and stochastics for EEs.......2007-05-10

Used this for a course.
It is pretty good to learn the basics from, although it gets pretty deep pretty fast by the fifth chapter or so, at which point you may need to use other references to help you stay afloat. Contains a lot of good sideitems that other books don't capture, and some decent examples. Lots of emphasis on DSP, a plus if that is what you are using this material for. Yates and Goodman is good as a companion if you need help understanding the basics. Papoulis is a good companion text for the advanced stuff.

Wow..........2007-04-05

I am amazed that this book is used as a primary text at so many universities. While initially I was unsure if this was a poor text, or if I was simply not adequately prepared to take a probability course, I qucikly realized upon viewing other references that this book was useless and that there are so many other books on this subject which address probability in an intuitive manner. I sometimes read this book and wonder who the authors were writing this book for. The examples are completely overbearing in some cases. Take Example 5.5-3, which was a 4 page discourse on Black Lung, which was probably pulled out of a journal paper. While this could be an interesting topic in probability, it is frustrating, confusing and discouraging to someone trying to learn the subject. I will not even go into the books typographical errors, as they have been mentioned in several other reviews. My advice would be to check out other references if you are taking a class using this text. This book is useful only to people who have mastered the subject.

Some good some bad.......2007-01-20

I found this book to be terrible when I was looking for something specific, but good if read from the start to finish of each chapter. My style of studying doesn't mesh well with the book's lack of a useful index and procedural organization within the text. The index is useless because common, major terms refer to pages that almost exclusively off-handedly mention the term with no further explanation. This organization makes it nearly useless as a reference book.

Great random processes book for engineers.......2005-11-13

This book is ideal as a textbook in a class on random processes, particularly for engineers and those interested in signal processing and telecommunications. I have found the book very easy to follow, quite accessible and complete, and the example problems are very indicative of the approach you need to solve the exercises at the end of each chapter. I would not recommend this book for self-study, however, as I think that self-study of a subject as difficult as random processes would be tough going for anybody. The criticisms that I would make are:
1. The book is poorly edited. There are a moderate number of typos. Some are in places where it is obvious what the author meant, but a few are in critical equations that could mislead the reader.
2. There are no solutions to any of the exercises included in the book. It would really help if there were solutions to either odd or even problems included so that you would know you are on the right path.
Since Amazon does not currently show the table of contents for this book, I do so for the purpose of completeness:
Chapter one is an introduction to probability. This material is covered quickly, so the reader should just use this as a review.
Chapter two introduces random variables. Included topics are the definition of a random variable, the probability density and distribution functions. This material is presented with exceptional clarity.
Functions of Random Variables are introduced in chapter three. This is one of the hardest chapters in the book, although I have not been able to find another book that explains the same material as well. This is mainly concerned with finding the probability density functions of f(x) and f(x,y) given the pdf of the input functions. Convolution and multiple integrals abound in this chapter.
Chapter 4 is Expectation and Introduction to Estimation. This sounds straightforward, but the material on conditional expectation can get complex, although the book covers it well.
Chapter 5 is Random Vectors and Parameter Estimation. This chapter takes concepts from numerical linear algebra and applies it to random processes.
Chapter six is random sequences and introduces linear systems concepts and markov processes.
Chapters seven and eight talk about advanced concepts in random processes.
Chapter nine discusses applications of the previous eight chapters to statistical signal processing.
To get the most out of this book you should already be familiar with probability theory, multiple variable calculus, and linear algebra. If you are not, there is no way you are going to understand this material. A good companion to this book is Schaum's outline of Probability, Random Variables, and Random Processes. It covers most of the same material as this book, except that it does so with more of a mathematician's viewpoint. The Schaum's outline's solved problems also help offset the fact that there are no solutions to exercises in this book. Just remember that there is no textbook on a subject as complex as random processes that is going to negate the need for an instructor of exceptional ability.

Well written but lacks editing, a bit sloppy.......2005-03-13

This book is well written, and is especially interesting for electrical engineers because it uses examples from their field almost from the start. However, it is rife with typos, which can be frustrating in a math book, where you often assume its true, then try to figure out why. Also, it exhibits the sloppy math style common to engineers, especially when it comes to the distinction between constants and variables. This can lead to alot confusion at first.

Average customer rating:

Fundamental book discovering new horizons in micromechanics
A modern and comprehensive treatise of material properties

Random Heterogeneous Materials
Salvatore Torquato
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover

General | Engineering | Professional & Technical | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

General | Physics | Science | Subjects | Books

General | Medicine | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Medicine | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Accessories:

ASIN: 0387951679

Book Description

The overall aim of this book is to provide a rigorous means to characterize the microstructure and properties of heterogeneous materials that can simultaneously yield results of practical utility. A unified treatment of both microstructure and properties is emphasized. The book is divided into two parts. Part I deals with the quantitative characterization of the microstructure of heterogeneous via theoretical, computer-simulation and imaging techniques. Emphasis is placed on theoretical methods. Part II treats a wide variety of effective properties of heterogeneous materials and how they are linked to the microstructure. This is accomplished using rigorous methods. Wherever possible, theoretical predictions for the effective properties are compared to available, experimental and computer-simulation data. This book will be of interest to graduate students and researchers in applied mathematics, physics, chemistry, materials science and engineering.

Customer Reviews:

Fundamental book discovering new horizons in micromechanics.......2001-12-30

The micromechanics of random structure heterogeneous materials is a multidisciplinary research area that has experienced a revolutionary renascence at the overlap of various branches of materials science, mechanical engineering, applied mathematics, technical physics, geophysics, and biology. The present book is a perfect reflection of this overlapping. It demonstrats intriguing successes of unified rigorous theoretical methods of applied mathematics and statistical physics in material science of microheterogeneous media. The prediction of the behavior of heterogeneous materials by the use of properties of constituents and their microstructure is a central problem of micromechanics. This book is the first one in micromechanics where a successful effort of systematic and fundamental research of the microstructure of the wide class of heterogeneous materials of natural and synthetic nature is attempted. The uniqueness of the book by Torquato consists of the development and expressive representation of statistical methods quantitatively describing random structures (first part of the book) which are at most adopted for the forthcoming evaluation of a wide variety of macroscopic transport, electromagnetic, elastic, and chemical properties of heterogeneous materials (second part of the book). The popular methods in micromechanics that are essentially one particle ones which are invariant with respect to statistical second and higher order quantities examining the association of one particle relative to other particles. The book by Torquato expressively reflects the explosive character of progress of the modern micromechanics caused by the development of image analyses and computer-simulation methods from one side and improved materials processing from the other hand, since processing controls the prescribed microstructure. This progress in micromechanics is based on the methods of allowing for the statistical mechanics of a multi-particle system considering n-point correlation functions and direct multi-particle interaction of inclusions, and the book presents a universally rigorous scheme of both analyses of the microstructures and prediction of macroscopic properties which leaves room for corrections of their individual elements if improved methods are utilized for the analysis of these individual elements.

This book is a landmark in the area of advanced heterogeneous materials and constitutes an excellent balance of depth and clarity of their representation. Every science library and every individual involved in serious research in heterogeneous materials must have this book which will be interesting for both advanced senior scientists and graduate students.

A modern and comprehensive treatise of material properties.......2001-11-13

I had the opportunity to use this text while taking Prof. Torquato's material science course at Princeton. The classnotes were a condensed version of the book, while the book describes all the concepts in more details. The book presents a unified treatment of the basic equations of continuum mechanics (flow, elasticity, conduction, diffusion) from a statistical mechanical viewpoint (heavy use of probability models is made), in composite materials (for example, a material with 'spherical inclusions' of a different physical electrical conductivity from the surrounding medium are added) characterized by effective properties (conductivity, permeability, stiffness, trapping constant). The effective properties are calculated from first principles via various correlation functions (Section I describes the probability functions required for dealing with random media; Section II deals with actual calculations of effective properties). To my knowledge, it is the first comprehensive book on the subject; other texts deal with smaller subsections. In some cases, these techniques were previously available only in the specialized literature. I found the many examples provided in the text to be very helpful. I also enjoyed the section on variational principles in the second half of the book; it provides further examples of how variational calculus can be applied to solve relevant problems (in this case, dealing with the optimization of material properties). Most of the theorems are proved and the proofs are short and so shouldn't be much of a burden. The chemist should know this is mostly a book on mathematics, and so does not provide numerical examples with numbers and units (however, all one needs to do is plug in numbers in the formulas), and doesn't present too many actual real-life physical examples you are likely to deal with in the laboratory. Prerequisites are simple: a bit of linear algebra, tensor calculus (but only in orthogonal euclidean spaces), familiarity with basics of probability theory (you should know what a probability density is). Knowledge of statistical mechanics is helpful but not required. There is, of course, a section on hard sphere packing for which the author is well-known for. The chapter on homogenization theory is one of the most accessible I've seen (no knowledge of functional analysis is required-- so it is perfect for the beginner). This book does not have exercises or problems for the reader (it is not for the undergraduate student-- but rather for researchers in the cross-disciplinary fields), and so requires a certain degree of maturity to absorb the material.