A Student’s Guide to Data and Error Analysis (Student’s Guides) 1st Edition by Herman J. C. Berendsen (PDF)

Description

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.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐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.

⭐Excellent book! It’s full of very useful and practical information.

⭐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 central limit theorem can be found in almost all textbooks on statistics, its proof is almost never given”. In this book this theorem is demonstrated at one of the many appendices.

⭐Really good, but somehow I believe that it is slightly difficult for a student’s guide. Any measurement error must be considered in any experiment and the chapter on Distributions is a must in probability and inferential statistics. Many sections as Appendices complete this guide along with a whole section on the Central Limit Theorem which is highly important in probability. I recommend this book because of its detail and rigour.

⭐Good

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