000			02840cam a2200325Ia 4500
001			0000048523
003			0001
008			061102s2006 caua s 000 0 eng d
020			_a9781598291513
020			_a9781598291506 (pbk.)
082	0	4	_a519.2 _222
084			_a519.2 _bEND-A
100	1		_aEnderle, John D. _q(John Denis)
245	1	0	_aAdvanced probability theory for biomedical engineers _h[Book] / _cJohn D. Enderle, David C. Farden, Daniel J. Krause.
250			_a1st ed.
260			_a[San Rafael, Calif.] : _bMorgan & Claypool Publishers, _cc2006.
300			_aviii, 100 p. : _bill ; _c25 cm.
490	1		_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v#11.
500			_aTitle from PDF t.p. (viewed on Nov. 2, 2006).
500			_a"This is the third in a series of short books on probability theory and random processes for biomedical engineers"--Abstract.
520			_aThis is the third in a series of short books on probability theory and random processes for biomedical engineers. This book focuses on standard probability distributions commonly encountered in biomedical engineering. The exponential, Poisson and Gaussian distributions are introduced, as well as important approximations to the Bernoulli PMF and Gaussian CDF. Many important properties of jointly Gaussian random variables are presented. The primary subjects of the final chapter are methods for determining the probability distribution of a function of a random variable. We first evaluate the probability distribution of a function of one random variable using the CDF and then the PDF. Next, the probability distribution for a single random variable is determined from a function of two random variables using the CDF. Then, the joint probability distribution is found from a function of two random variables using the joint PDF and the CDF. The aim of all three books is as an introduction to probability theory. The audience includes students, engineers and researchers presenting applications of this theory to a wide variety of problems as well as pursuing these topics at a more advanced level. The theory material is presented in a logical manner developing special mathematical skills as needed. The mathematical background required of the reader is basic knowledge of differential calculus. Pertinent biomedical engineering examples are throughout the text. Drill problems, straightforward exercises designed to reinforce concepts and develop problem solution skills, follow most sections.
521			_aAll.
650		0	_aProbabilities.
650		0	_aRandom variables.
650	1	2	_aProbability Theory.
650	2	2	_aBiomedical Engineering.
700	1		_aFarden, David Charles.
700	1		_aKrause, Daniel J.
852			_p30005 _90.00 _dBooks
999			_c151560 _d151560