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A Student's Guide to Data and Error Analysis, by Herman J. C. Berendsen
Download Ebook A Student's Guide to Data and Error Analysis, by Herman J. C. Berendsen
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All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
- Published on: 2012-06-05
- Binding: Printed Access Code
Review
"Overall, this would be a nice text or reference to accompany a short course in statistics for undergraduate science or engineering..also useful for researchers desiring a primer or review...Recommended." - CHOICE
About the Author
Herman Berendsen is Emeritus Professor of Physical Chemistry at the University of Groningen, the Netherlands. His research started in nuclear magnetic resonance but focused later on molecular dynamics simulations on systems of biological interest. He is one of the pioneers in this field and, with over 35,000 citations, is one of the most quoted authors in physics and chemistry. He has taught courses in molecular modeling worldwide and authored the book Simulating the Physical World (Cambridge University Press, 2007).
Most helpful customer reviews
7 of 7 people found the following review helpful.
Nice book of recipies but not more
By Luis Isaac Ramos Garcia
This book is more a collection of statistical recipes about data analysis than a proper book about that topic. In fact the space devoted to the appendices is comparable to the space of the core.
If this is the intention of the reader, this book is fine, but if the reader looks for something more advanced, and wants to know where the recipes came from, this is not the right book. In this case are better books exist for example Statistical Data analysis by G. Cowan or Data reduction and error analysis for the physical sciences by P. R. Bevinton and D. K. Robinson.
There are few examples in the book, although some problems are proposed at the end of last chapter with answered at the middle of the book, between the core and the appendices.
I am in agreeing with the authors claim: "While the limit theorem can be found in almost all textbooks on statics, its proof is almost never given". In this book this theorem is demonstrated at one of the many appendices.
0 of 0 people found the following review helpful.
The perfect companion to anyone involved in the data sciences
By Kai Staats
The perfect companion to anyone involved in the data sciences. It sits on my desk, or is thrown in my backpack with my laptop as companion for my work in machine learning.
0 of 0 people found the following review helpful.
Great book!
By WDP
Excellent book! It's full of very useful and practical information.
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