000			04203nam a2200709 i 4500
001			6813014
003			IEEE
005			20200413152845.0
006			m eo d
007			cr cn |||m|||a
008			061030s2006 caua ob 000 0 eng d
020			_a1598291416 (ebook)
020			_a9781598291414 (ebook)
020			_a1598291408 (paper)
020			_a9781598291407 (paper)
024	7		_a10.2200/S00062ED1V01Y200610BME010 _2doi
035			_a(CaBNVSL)gtp00531407
035			_a(OCoLC)74651742
040			_aGAT _cGAT _dCaBNVSL
050		4	_aQA273 _b.E583 2006
082	0	4	_a519.2 _222
090			_a _bMoCl _e200610BME010
100	1		_aEnderle, John D. _q(John Denis)
245	1	0	_aIntermediate probability theory for biomedical engineers _h[electronic resource] / _cJohn D. Enderle, David C. Farden, Daniel J. Krause.
250			_a1st ed.
260			_aSan Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) : _bMorgan & Claypool Publishers, _cc2006.
300			_a1 electronic text (vii, 106 p. : ill.) : _bdigital file.
490	1		_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v10
538			_aSystem requirements: Adobe Acrobat Reader.
538			_aMode of access: World Wide Web.
500			_aSeries from website.
500			_aPart of: Synthesis digital library of engineering and computer science.
504			_aIncludes bibliographical references (p. 105-106).
505	0		_aExpectation -- Moments -- Bounds on probabilities -- Characteristic function -- Conditional expectation -- Summary -- Problems -- Bivariate random variables -- Bivariate CDF -- Bivariate Riemann-Stieltjes integral -- Expectation -- Convolution -- Conditional probability -- Conditional expectation -- Summary -- Problems.
506	1		_aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510	0		_aGoogle book search
510	0		_aGoogle scholar
510	0		_aINSPEC
510	0		_aCompendex
520			_aThis is the second in a series of three short books on probability theory and random processes for biomedical engineers. This volume focuses on expectation, standard deviation, moments, and the characteristic function. In addition, conditional expectation, conditional moments and the conditional characteristic function are also discussed. Jointly distributed random variables are described, along with joint expectation, joint moments, and the joint characteristic function. Convolution is also developed. A considerable effort has been made to develop the theory in a logical manner -- developing special mathematical skills as needed. The mathematical background required of the reader is basic knowledge of differential calculus. Every effort has been made to be consistent with commonly used notation and terminology both within the engineering community as well as the probability and statistics literature. The aim is to prepare students for the application of this theory to a wide variety of problems, as well give practicing engineers and researchers a tool to pursue these topics at a more advanced level. Pertinent biomedical engineering examples are used throughout the text.
530			_aAlso available in print.
588			_aTitle from PDF t.p. (viewed on Oct. 29, 2008).
650		0	_aProbabilities.
650		0	_aRandom variables.
650		0	_aBiometry.
690			_aCharacteristic function.
690			_aProbability theory.
690			_aRandom processes.
690			_aEngineering statistics.
690			_aProbability and statistics for biomedical engineers.
690			_aStatistics.
690			_aBiostatistics.
690			_aExpectation.
690			_aStandard deviation.
690			_aMoments.
700	1		_aKrause, Daniel J.
700	1		_aFarden, David Charles.
730	0		_aSynthesis digital library of engineering and computer science.
830		0	_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v#10.
856	4	2	_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6813014
856	4	2	_3Abstract with links to resource _uhttp://dx.doi.org/10.2200/S00062ED1V01Y200610BME010
999			_c561514 _d561514