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on April 20, 2011
I'm a grad student and I recently had to learn how to numerically solve PDE's. I'm rather new to computer programming and numerical analysis in general. I've really only been in my field for about 1 year now.

I picked up this book and went straight to Chapter 12. It explained everything quite concisely and had very clear descriptions and diagrams. Armed with pen and paper, I learned how to numerically solve these PDE's quite quickly. It was honestly a fun experience. Whenever there were tools that I was missing, the authors would reference the section and chapter where you could find the necessary tools.

I believe this book was written as a reference, as well as, textbook. A problem that many textbooks suffer from, is that the material is written in sequential order, with newer material depending heavily on the previous chapters. These types of books are not adept to being just picked up and read, to gather the relevant information. They require you to pretty much read all the preceding text to understand it, and who has time for that? This book is NOT like that.

You can just pick it up and easily learn from it. Unlike Numerical Recipes, this provides the method with a very clear explanation and justification for the algorithms. Numerical Recipes is good, but its purpose is not to provide detailed explanations of why and how the algorithms work.

To be able to use this text, I would suggest having taken Calc 1,2 & 3, differential equations, linear algebra class, and be comfortable with programming. I suspect that the folks complaining heavily about this text, are not very comfortable with with Calculus, linear algebra, and/or programming. If you are an undergrad and have not taken those classes or are not comfortable with the material, I can see you struggling. If you are a grad student in Math or Physics, this text will be rather refreshingly easy to read. It will help fill in the necessary gaps in your knowledge of computational work, if you have any like I did. Enjoy!
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on April 8, 2014
I'm Biased since I had Richard Burden(Author) as my professor for Numerical Analysis and this is the book we used in his course (obviously).

I doubt you'll be looking into any of these books unless you need a reference material for a course or something, but there wasn't significant differences between this version and the next one. But from what I understand the most recent version has enough differences that if you need this for a course, to get the newest version. But, if you are just buying this for your own sake, this is a great book/version.

The material in the book itself is a great resource, and I would argue that any CS student (or even just programmer who wants to be a bit better in his field) should know this material, that way they know how to evaluate run-time performance of a program (if nothing else). The book is fairly well understandable even if you aren't the best in math, so don't let that stop you if you are interested, there are online code snippets and evaluation programs you can try out and learn from also.
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on October 2, 2013
By reading the material in this book, the student is left with the theory and the examples necessary to understand and appreciate Numerical Methods in Engineering. There is no need to memorize formulas. Most students, with little bit of effort, can derive their own formulas to solve a specific problem. While the book is starting as a Numerical Methods Textbook, yet it helps the student to smoothly enter the world of Numerical Analysis. The topics included are more than enough for a two semester course presented in an easy-to-read style with lots of solved examples. I have been teaching Numerical Methods and Numerical Analysis for many years now and have found that this textbook provides adequate background and the necessary skills for my students. This book teaches how to derive numerical solutions to problems. That is perhaps the most important lesson of all.
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on August 9, 2016
Fantastic reference for anyone with a solid mathematical background and in a research field requiring data analysis.
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on January 4, 2017
As described.
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on November 3, 2014
Required textbook for a course in Numerical Analysis. I would probably seek another reference if given an opportunity, but that means I would have to read a lot of dry books to get there. It has some good sample code to assist in understanding the development of certain algorithms.
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on October 20, 2011
If you're not buying this for a class, you might be looking for one or both of the following:
* an explanation of the mathematical tools and methods used in developing numerical algorithms, or
* a guide to the intricacies and pitfalls of implementing numerical algorithms for scientific computing.

For either of these cases, this is not the book you want. The algorithms and theorems have little motivation, and when there are several alternative algorithms to choose from there is little or no discussion of which is more appropriate under what circumstances. The pseudocode is enough to write a working version in whatever language in order to do the exercises, but it's not at all helpful for creating efficient and robust code that will be reused.

If you just want an overview of numerical analysis and the various basic algorithms this might not be a terrible choice except for the countless errors in the book, including the solutions in the back.
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on April 20, 2012
This textbook was used in an undergraduate numerical analysis course in which I was a student, and first and foremost, there are a few caveats I should say before I proceed any further... this was an intro level course with the only prerequisites being multivariable calculus and linear algebra, it was taught from a more "doing all the work by hand" approach rather than using software (which is rather uncommon for a course in numerical analysis), and we only covered five of the first six chapters of the text (chapter 5, covering ODEs, was omitted). But even if we had gone further, I have to say that I feel that the book had some serious shortcomings.

As mentioned, we didn't use much software in the course, and this (as it should be) is somewhat focused on using software and algorithms for the course. However, I feel too often in this book, all that was really being taught was how to input everything into the various programs out there, and pulling out a result... without actually knowing what is going on and why the results turn out the way that they do. It is an undeniable fact that much of numerical analysis takes place using computers, but an introductory level text (as this one is) should at the very least strive to explain how each process works, and not just "hand wave" and tell students to input data in Maple. Many times, the book would give a theorem or equation (often buried deep inline with the text) and not really focus much on what the meaning of the theorem is, or how to apply it when doing calculations by hand. That is certainly fine for an engineering based course in numerical analysis (which mine was NOT), but for mathematics students wanting to know the theory, it doesn't help to just throw in a theorem, then start giving examples. And speaking of examples, that leads to another problem that this text seems to have. Much of the teaching which it does is by example. It simply gives examples and expects you to more or less just follow the example and substitute values in here and there if you are doing it on your own. Examples are great, particularly in an introductory level text, but when you simply follow examples, what are you truly learning? The chapter on interpolation (chapter 3) was particularly terrible about this, and got worse as the chapter went on. The section on the cubic spline will always stand out to me as one of the most poorly written sections I've seen in a textbook in my entire life. The material isn't too difficult, but if you attempt to follow what the book has, you will be lost beyond all hope.

Oddly enough, though, even though our course wasn't software based, we weren't discouraged from USING software to "play around" with some of the problems to compare our own results to what was obtained in the software. My experience, though, was that the codes written for Maple and MATLAB always seemed to simply not work. At all. I was usually able to use most of the Java applets provided by the author's website without much trouble, but I honestly can't say that the applets provided very insightful or meaningful results.

If there is anything positive that I can say about the book, it is that, despite the shortcomings in explaining anything, I felt that the exercises provided in each section were decent, providing a variety of exercises for different groups of students, and even including some exercises on theoretical stuff which would serve even pure mathematicians rather well. But even the exercises have a problem, and perhaps it is because numerical analysis is often a software-based course, and that is the fact that it mixes exercises which can easily be done with pencil, paper, and a basic scientific calculator (i.e. the way the course that I took was focused) with exercises which require hundreds (literally) of calculations... in other words, they MUST be done by software. A clear indication of exercises which should be done by software would have been nice, as is common in many textbooks.

All of that being said, with an effective instructor, this textbook does have some use, but if you are attempting to learn the material on your own, you will be completely lost with this textbook almost immediately following the second chapter (the first two chapters do have SOME clarity, but those are rather simple topics).
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on October 30, 2010
I am using this book for a grad numerical methods class for a masters program in mechanical engineering. The book does not explain very well some of the steps taken during some of examples shown. But it goes into some heavy duty math proofs and concepts. Yeah I like advanced math like the next guy but I think they should spend more time and paper space on algorithms and code definitions as their algorithms are spotty. And some of the Matlab code that is provided on their website does not work. This is a Numerical Analysis book and if they provide programming code then it should work. I spent too much time trying to debug their code that I gave up and started writing my own. So my advice to other people is to study the algorithms shown in the book, come up with a cleaner/better algorithm and write your own code. Do that and then the book will get you through.
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on February 4, 2011
This paperback book is extremely helpful for getting through this course. It explains things very well and is a great reference for when you get stuck. My only problem is that only part of the questions are worked out. It's not all odds, for example: 1,2,4,5,9,14,16,24,28 are the questions answered for 1.1. It seems that they are the best questions, the ones most likely to be selected by the professor. Every now and then I'll come across a difficult question that got skipped over by this book and it becomes a little aggravating.

Overall, this book is a giant help and is completely worth the $50 that I paid.
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