000			03436nam a22004575i 4500
001			978-3-642-03305-6
003			DE-He213
005			20140220084525.0
007			cr nn 008mamaa
008			100715s2010 gw | s |||| 0|eng d
020			_a9783642033056 _9978-3-642-03305-6
024	7		_a10.1007/978-3-642-03305-6 _2doi
050		4	_aQC5.53
072		7	_aPHU _2bicssc
072		7	_aSCI040000 _2bisacsh
082	0	4	_a530.15 _223
100	1		_aGrabe, Michael. _eauthor.
245	1	0	_aGeneralized Gaussian Error Calculus _h[electronic resource] / _cby Michael Grabe.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_aXIII, 301p. 100 illus., 50 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aBasics of Metrology -- True Values and Traceability -- Models and Approaches -- Generalized Gaussian Error Calculus -- The New Uncertainties -- Treatment of Random Errors -- Treatment of Systematic Errors -- Error Propagation -- Means and Means of Means -- Functions of Erroneous Variables -- Method of Least Squares -- Essence of Metrology -- Dissemination of Units -- Multiples and Sub-multiples -- Founding Pillars -- Fitting of Straight Lines -- Preliminaries -- Straight Lines: Case (i) -- Straight Lines: Case (ii) -- Straight Lines: Case (iii) -- Fitting of Planes -- Preliminaries -- Planes: Case (i) -- Planes: Case (ii) -- Planes: Case (iii) -- Fitting of Parabolas -- Preliminaries -- Parabolas: Case (i) -- Parabolas: Case (ii) -- Parabolas: Case (iii) -- Non-Linear Fitting -- Series Truncation -- Transformation.
520			_aFor the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence interval as put down by Student, and a contribution due to unknown systematic errors, as expressed by an appropriate worst case estimation.
650		0	_aPhysics.
650		0	_aSystems theory.
650		0	_aMathematical physics.
650		0	_aEngineering.
650	1	4	_aPhysics.
650	2	4	_aMathematical Methods in Physics.
650	2	4	_aSystems Theory, Control.
650	2	4	_aEngineering, general.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642033049
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-03305-6
912			_aZDB-2-PHA
999			_c111486 _d111486