Intermediate probability theory for biomedical engineers
By: Enderle, John D. (John Denis).
Contributor(s): Krause, Daniel J | Farden, David Charles.
Material type:
BookSeries: Synthesis lectures on biomedical engineering: #10.Publisher: San Rafael, Calif. (1537 Fourth St, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2006Edition: 1st ed.Description: 1 electronic text (vii, 106 p. : ill.) : digital file.ISBN: 1598291416 (ebook); 9781598291414 (ebook); 1598291408 (paper); 9781598291407 (paper).Uniform titles: Synthesis digital library of engineering and computer science. Subject(s): Probabilities | Random variables | Biometry | Characteristic function | Probability theory | Random processes | Engineering statistics | Probability and statistics for biomedical engineers | Statistics | Biostatistics | Expectation | Standard deviation | MomentsDDC classification: 519.2 Online resources: Abstract with links to resource | Abstract with links to resource Also available in print.| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
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PK Kelkar Library, IIT Kanpur | Available | EBKE014 |
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.
Series from website.
Part of: Synthesis digital library of engineering and computer science.
Includes bibliographical references (p. 105-106).
Expectation -- 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.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
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Compendex
This 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.
Also available in print.
Title from PDF t.p. (viewed on Oct. 29, 2008).
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