000			02769nam a22004335i 4500
001			978-3-642-11589-9
003			DE-He213
005			20140220084531.0
007			cr nn 008mamaa
008			100623s2010 gw | s |||| 0|eng d
020			_a9783642115899 _9978-3-642-11589-9
024	7		_a10.1007/978-3-642-11589-9 _2doi
050		4	_aT50
072		7	_aPDDM _2bicssc
072		7	_aSCI068000 _2bisacsh
082	0	4	_a530.8 _223
100	1		_aWolberg, John. _eauthor.
245	1	0	_aDesigning Quantitative Experiments _h[electronic resource] : _bPrediction Analysis / _cby John Wolberg.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_aXII, 208p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aStatistical Background -- The Method of Least Squares -- Prediction Analysis -- Separation Experiments -- Initial Value Experiments -- Random Distributions.
520			_aThe method of Prediction Analysis is applicable for anyone interested in designing a quantitative experiment. The design phase of an experiment can be broken down into problem dependent design questions (like the type of equipment to use and the experimental setup) and generic questions (like the number of data points required, range of values for the independent variables and measurement accuracy). This book is directed towards the generic design phase of the process. The methodology for this phase of the design process is problem independent and can be applied to experiments performed in most branches of science and technology. The purpose of the prediction analysis is to predict the accuracy of the results that one can expect from a proposed experiment. Prediction analyses can be performed using the REGRESS program which was developed by the author and can be obtained free-of-charge through the author's website. Many examples of prediction analyses are included in the book ranging from very simple experiments based upon a linear relationship between the dependent and independent variables to experiments in which the mathematical models are highly non-linear.
650		0	_aPhysics.
650		0	_aEngineering.
650	1	4	_aPhysics.
650	2	4	_aMeasurement Science and Instrumentation.
650	2	4	_aEngineering, general.
650	2	4	_aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642115882
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-11589-9
912			_aZDB-2-PHA
999			_c111885 _d111885