000			02772nam a22003498i 4500
001			CR9780511921247
003			UkCbUP
005			20200124160258.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			100927s2011||||enk o ||1 0|eng|d
020			_a9780511921247 (ebook)
020			_z9780521119405 (hardback)
020			_z9780521134927 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA275 _b.B43 2011
082	0	0	_a511/.43 _222
100	1		_aBerendsen, Herman J. C., _eauthor.
245	1	2	_aA student's guide to data and error analysis / _cHerman J.C. Berendsen.
246	3		_aA Student's Guide to Data & Error Analysis
264		1	_aCambridge : _bCambridge University Press, _c2011.
300			_a1 online resource (xii, 225 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aPart 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 the 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.
520			_aAll 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.
650		0	_aError analysis (Mathematics)
776	0	8	_iPrint version: _z9780521119405
856	4	0	_uhttps://doi.org/10.1017/CBO9780511921247
999			_c520175 _d520173