An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements

This book does an excellent job of starting from the basics and then building on them at a comfortable pace until the reader has been taken to the more advanced and useful points of error analysis. This book is clearly written, with appropriate and helpful examples throughout. The practice problems at the end of the chapters are relevant and straightforward, further aiding the learning process. The author not only understands the subject of error analysis inside and out, he also knows the right way to teach it. Though the book approaches error analysis from a physics point of view, I found it very applicable to all of my scientific coursework, including biochemistry and (especially) analytical chemistry.

An excellent introduction to error analysis: it's well written, all the ideas are explained at an intuitive level and with an easy-to-understand language; furthermore no mathematical prerequisites of high level are requested. The level is appropriate to undergraduate student, but it remains a very good book for consultation at higher level, too.

Very very good binding and hardcover: it's durable and solid, with an excellent value for money. Remark that on the internal part of the hard cover (the two first and the two last pages) it's present a short summary on the most essential formulas, which are very useful for speedy consultation.

Everyone who does and will design, execute and/or post-analyze measurements, regardless of where - classroom or real -, should read this book. I've studied statistics and probabilities and took a number of engineering and physical science classes, but none gave me such a coherent view of the problem and how to approach it. This book gives you the first clear & definite step forward with the subject.

This is no doubt a great book on error analysis for scientists and engineers, especially for those who are very interested in working in a lab. The content is very detailed and specific. This book contains a lot of fine examples and exercising problems. The back of the book provides solutions to some of the problems (odd-numbered ones).

This book is perfect for somebody who was never properly introduced to formal probability and statistics. The language is easy to understand and each chapter not only explains the "what," but makes sure you understand the "why" as well. Also introduces you to more complicated aspects of the subject--binomial & poisson distributions, chi-squared analysis, etc.

This will never rise to the level of his Classical Mechanics book, because the material is nowhere as interesting. Yet any student of experimental science must at some point be confronted to question the quality of their data, and in most instances, rigorous error analysis is never formally taught. The high clarity of this book makes it perfect for self study.

I've read and studied more than my fair share wrt error analysis and uncertainty propagation. Hands down this is the best I've ever seen.

It was what I needed, a great book, easy to follow, I advise this book as a great support for those who are willing to study statistics and error estimation in the experimental work.

I have no formal science training, just what I've managed to teach myself studying used physics texts from the thrift store, and books from the popular press (especially Asimov non-fiction -- most highly recommended !!) Believe you me, if even a dunce such as myself can "get" error analysis from a book such as this one, anyone can!

Taylor starts with the simplest, most basic, yet so utterly necessary concepts such as: What is a measurement? How are measurements performed? What sorts of errors can occur in measurement? How may they be quantified and compared? And most importantly, yet all-too-often neglected: How do I go about presenting (graphing) my results to my science colleagues in a meaningful and convincing manner?

He goes on from there, introducing new concepts atomically, one at a time, building up to statistical methods of interpreting experimental results. The opening chapters are so simple a gradeschooler could get started with this book; however, as concept builds upon concept with each succeeding chapter, the material smoothly becomes quite challenging. The later chapters in the book become quite formidable, and I had to go back to earlier chapters to refresh my understanding of the rudiments to continue. But that was my own fault because I rushed through what I thought at the time was "too-easy" material and let too much time elapse between chapters. This is actually a testament to the quality of Taylor's presentation: everything I ever needed was in the book and I never had to supplement it with outside research.

Each chapter ends with several paragraphs of summary and several pages of problem exercises. The reader should not give in to any temptation to skip these over, because Taylor reviews his material with a slightly different emphasis that I find greatly aids comprehension. He also uses this space to highlight how the new material fits in with what went before. In some of the sample problems, he also takes opportunity to present new little tidbits of information that pertain to that chapter's material. The reader must pay close attention to catch these little gems because Taylor effectively sneaks them into his posing of the problem, but never fear, he doesn't use this gimmick for anything really important, -- just for bonus info.

For a subject area that seemed so daunting as analysis of experiemental results, I was most fortunate to have chanced upon this excellent text! I'd give six stars if I could.

fine book