A student's guide to data and error analysis - Info and Reading Options
By Herman J. C. Berendsen
"A student's guide to data and error analysis" was published by Cambridge University Press in 2011 - Cambridge, it has 225 pages and the language of the book is English.
“A student's guide to data and error analysis” Metadata:
- Title: ➤ A student's guide to data and error analysis
- Author: Herman J. C. Berendsen
- Language: English
- Number of Pages: 225
- Publisher: Cambridge University Press
- Publish Date: 2011
- Publish Location: Cambridge
“A student's guide to data and error analysis” Subjects and Themes:
- Subjects: ➤ TECHNOLOGY & ENGINEERING / Engineering (General) - Error analysis (Mathematics) - Physical sciences - Engineering, statistical methods - Engineering, handbooks, manuals, etc. - Technology & engineering / engineering (general) - Error analysis (mathematics)
Edition Specifications:
- Pagination: xii, 225 p. :
Edition Identifiers:
- The Open Library ID: OL25551605M - OL16953539W
- Online Computer Library Center (OCLC) ID: 663441088
- Library of Congress Control Number (LCCN): 2010048231
- ISBN-13: 9780521119405 - 9780521134927
- ISBN-10: 0521119405 - 0521134927
- All ISBNs: 0521119405 - 0521134927 - 9780521119405 - 9780521134927
AI-generated Review of “A student's guide to data and error analysis”:
"A student's guide to data and error analysis" Table Of Contents:
- 1- Machine generated contents note: Part I. Data and Error Analysis: 1. Introduction; 2. The presentation of physical quantities with their inaccuracies; 3. Errors: classification and propagation; 4. Probability distributions; 5. Processing of experimental data; 6. Graphical handling of data with errors; 7. Fitting functions to data; 8. Back to Bayes: knowledge as a probability distribution; Answers to exercises; Part II. Appendices: A1. Combining uncertainties; A2. Systematic deviations due to random errors; A3. Characteristic function; A4. From binomial to normal distributions; A5. Central limit theorem; A6. Estimation of th varience; A7. Standard deviation of the mean; A8. Weight factors when variances are not equal; A11. Least squares fitting; Part III. Python codes; Part IV. Scientific data: Chi-squared distribution; F-distribution; Normal distribution; Physical constants; Probability distributions; Student's t-distribution; Units.
"A student's guide to data and error analysis" Description:
The Open Library:
"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"--
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