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Numerical Analysis, by Richard L. Burden, J. Douglas Faires
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The new Seventh Edition of Burden and Faires' well-respected Numerical Analysis provides a foundation in modern numerical-approximation techniques. Explaining how, why, and when the techniques can be expected to work, the Seventh Edition places an even greater emphasis on building readers' intuition to help them understand why the techniques presented work in general, and why, in some situations, they fail. Applied problems from diverse areas, such as engineering and physical, computer, and biological sciences, are provided so readers can understand how numerical methods are used in real-life situations. The Seventh Edition has been updated and now addresses the evolving use of technology, incorporating it whenever appropriate.
- Sales Rank: #648956 in Books
- Brand: Brand: Brooks Cole
- Published on: 2000-12-29
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 7.50" w x 1.50" l,
- Binding: Hardcover
- 841 pages
- Used Book in Good Condition
About the Author
Richard L. Burden is Emeritus Professor of Mathematics at Youngstown State University. His master's degree in mathematics and doctoral degree in mathematics, with a specialization in numerical analysis, were both awarded by Case Western Reserve University. He also earned a masters degree in computer science from the University of Pittsburgh. His mathematical interests include numerical analysis, numerical linear algebra, and mathematical statistics. Dr. Burden has been named a distinguished professor for teaching and service three times at Youngstown State University. He was also named a distinguished chair as the chair of the Department of Mathematical and Computer Sciences. He wrote the Actuarial Examinations in Numerical Analysis from 1990 until 1999.
J. Douglas Faires, late of Youngstown State University, pursued mathematical interests in analysis, numerical analysis, mathematics history, and problem solving. Dr. Faires won numerous awards, including the Outstanding College-University Teacher of Mathematics by the Ohio Section of MAA and five Distinguished Faculty awards from Youngstown State University, which also awarded him an Honorary Doctor of Science award in 2006.
Most helpful customer reviews
0 of 0 people found the following review helpful.
Five Stars
By Mike_Black
Fantastic reference for anyone with a solid mathematical background and in a research field requiring data analysis.
5 of 10 people found the following review helpful.
Confusing
By A Customer
This is an expensive math textbook which is confusing and has errors here and there. The answers to some of the exercises are incorrect. The algorithms provided in the text are very hard to understand and the code from the attached CD did not really match the algorithms in the book. If you're looking for a straightforward numerical analysis textbook, don't waste your money on this book like I did.
6 of 6 people found the following review helpful.
Good Refernce book
By lee
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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