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Data Reduction and Error Analysis for the Physical Sciences [Paperback]

Philip R. Bevington , D. Keith Robinson
4.0 out of 5 stars  See all reviews (20 customer reviews)


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Book Description

August 1, 2002 0071199268 978-0071199261 3rd
The purpose of this book is to provide an introduction to the concepts of statistical analysis of data for students at the undergraduate and graduate level, and to provide tools for data reduction and error analysis commonly required in the physical sciences. The presentation is developed from a practical point of view, including enough derivation to justify the results, but emphasizing methods of handling data more than theory. This text provides a variety of numerical and graphical techniques. Computer programs that support these techniques will be available on an accompanying website in both Fortran and C++.


Product Details

  • Paperback: 320 pages
  • Publisher: McGraw-Hill; 3rd edition (August 1, 2002)
  • Language: English
  • ISBN-10: 0071199268
  • ISBN-13: 978-0071199261
  • Product Dimensions: 0.5 x 6.2 x 9 inches
  • Shipping Weight: 1 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (20 customer reviews)
  • Amazon Best Sellers Rank: #1,554,791 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews
62 of 63 people found the following review helpful
5.0 out of 5 stars "Updated" classic, but still vintage '92 January 5, 1998
By A Customer
Format:Paperback
Robinson's second edition continues the late Bevington's tradition of clear and concise writing, making this book a priceless reference for scientists. Robinson has added discussions of modern problems such as resolving closely-spaced peaks in a spectrum. The new version also adds chapters on Monte Carlo techniques and maximum-likelihood analysis, both powerful tools for data analysis made possible by better computers.
The chapter structure has been modified considerably, so those who have grown comfortable with the first edition over the past decades may not be able to find things as easily. Other than that, most of the weaknesses are computer-related. Much has changed even since 1992.
Robinson added an appendix on graphical presentation. This sounds promising but is a pretty trivial discussion of when to use linear or logarithmic axes and the advantages of a historgram. Might be useful for a very young student, but these days playing with such things is easy in any graphing program.
Many of the computer code snippets have been removed. Most of them were only a few lines of code with lots of comment lines anyway. The codes that remain have been moved from the main text to a densely-packed appendix, which makes them more difficult to study while reading the text.
The codes themselves have been updated from old FORTRAN to a structured language, but I would have preferred C or FORTRAN 90 over the chosen PASCAL. The latter may be useful for undergraduate students, but I've never seen a PASCAL compiler in a working physics lab.
The included disk is a now-obsolete 5.25" floppy. I had to hunt for a machine that could read it and copy over to a 3.5" disc.
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13 of 14 people found the following review helpful
5.0 out of 5 stars Great Book May 22, 2002
By A Customer
Format:Paperback
I make measurements frequently and this book is great for providing the background to analyze your data.
I took undergraduate level statistics and it never really gave the practical applied background in how to analyze data. It merely presented concepts and presumed you knew how and why to apply them. This book is very good at helping you to understand the how and why.
I have read a number of other statistics book in search of the practical applied information provided in this book and did not find it in the other books.
The writing is clear and consice. There is enough background provided for even those unexposed to statistics.
I have not tried the software. Most of the formulas are easy to apply and can be implemented in simple programs or spreadsheets in very little time.
In short, I recommend this book to anyone making measurements of any kind.
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8 of 9 people found the following review helpful
2.0 out of 5 stars Buy Taylor's Book Instead December 13, 2009
Format:Paperback
Simply put, not as clear as John Taylor's error analysis book. If you want a good explanation for how and why to approach error analysis, this book does not do the job.
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7 of 8 people found the following review helpful
5.0 out of 5 stars All new but just as good July 25, 2004
Format:Paperback
This book seems to have been completely rewritten by the new author, only keeping the outline of the original, and it's for the better. The writing is as careful as the original, and as economical, so you have to master the early chapters or the rest is hopeless, as things start off slowly but quickly become difficult. It begins by considering the error in a single measurement, and proceeds to estimating errors derived from curve fitting. A few nuclear decay experiments provide examples throughout, and the author insists on calculating many quantities manually, even though in practice it would never be done that way. Some background topics like matrix algebra appear in the appendix too.
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4 of 4 people found the following review helpful
4.0 out of 5 stars An obscure error in a good book June 9, 2008
Format:Paperback|Verified Purchase
Bevington's book "Data Reduction and Error Analysis" is an old war-horse that is now in its third edition, and looks a good intermediate-level, practical reference to have on the shelf. I bought my copy only recently to follow up a reference, so am less familiar with it than I'd like to be before writing a review.

Unfortunately, following that reference led me to equation 4.22, which is wrong. When forming a weighted average of variances, one needs to square the weights in the numerator and square the sum of weights in the denominator. The equation as given has the first power of the weights and of the sum, just as found in the weighted mean. As I sort the matter out myself (with help from a friendly statistician) and look around at other treatments, this appears to be a common mistake, but mistake it is.

Otherwise, it seems a good book clearly written.
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3 of 3 people found the following review helpful
3.0 out of 5 stars Old Standard Marred by Terrible Editing December 15, 2011
By Brad W
Format:Paperback|Verified Purchase
This is a book that has been widely used by three generations of students and researchers. I used the 1969 edition as an undergraduate. The 2003 paperback edition would be an equally excellent publication except for the astounding number of editing errors in formulas and a few gross errors that seem to be outright mistakes. One particularly egregious error concerning multiplication of linear matrices appears in appendix B. I bought the text as a refresher and reference. Because I had a working knowledge of the subject matter, most of the errors were immediately evident. However, someone new to the subject would find many of them confusing.

In My opinion, McGraw Hill has done a terrible disservice to the authors and should be embarrassed at doing such a poor job of publishing an otherwise excellent book.
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Most Recent Customer Reviews
1.0 out of 5 stars A Lot of Fundamental Mistakes
This book contains a lot of fundamental mistakes. I’m not talking about typos that some people complain about. Read more
Published 4 months ago by Peter B
5.0 out of 5 stars A classic
This is a must for experimental science. Also the online avaible codes are great. I wrote a good nonlinear least squares program that can fit almost any function to data. Read more
Published 5 months ago by dgs
4.0 out of 5 stars In good condition
Book arrived in a timely manner and the used material was just as the summary described. I found it a good buy and satisfactory to my needs.
Published 6 months ago by Anthony
5.0 out of 5 stars The "Bevington" book
I still have the issue I came to use extensively back in the 70's - and I still do. This new version keeps on being useful for both the undergrad and grad student and for the... Read more
Published 8 months ago by Mariangela de Oliveira-Abans
5.0 out of 5 stars wonderful
I'm a grad student and this seems like a very useful book.... I learned about it in a meeting few weeks ago when one of my adviser's friends recommended me to buy it. Read more
Published 18 months ago by S. S. H.
5.0 out of 5 stars Really the Only Book
I had the good fortune to be trained by a physicist who, to my horror, left halfway through my bioinformatics PhD. Read more
Published on May 29, 2012 by Solanum
5.0 out of 5 stars Good Introduction to statistical analysis
I first read this book almost forty years ago when I was a physics major taking my first physics lab course. Read more
Published on February 7, 2011 by Ulfilas
5.0 out of 5 stars The bible of data analysis
When I joined Ed Stone's space radiation lab at Caltech, in 1978, he handed out copies of this book to every student working for him. It's still revised and reprinted today. Read more
Published on August 20, 2009 by D. Mitchell
5.0 out of 5 stars An Essential Book for Engineers and Scientists
As a practicing engineer, this was one of 5 or 6 books that I found most essential throughout my career. Chapter 4 on Propagation of Errors was referred to very often in my work.
Published on February 20, 2009 by Mr. James R. White
3.0 out of 5 stars Well...
You can tell he isn't an English major. The material is fine. A decent reference book.
Published on December 22, 2008 by Mathematics Man
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