Statistics for Engineering and Physical Science

PUBLISHED


Viewing: 1 - 10 of 120
Published:
May 02, 2013
Author(s):
Haym Benaroya; Seon Mi Han; Mark Nagurka
Now in its second edition, Probabilistic Models for Dynamical Systems expands on the subject of probability theory. Written as an extension to its predecessor, this revised version introduces students to the randomness in variables and time dependent functions, and allows them to solve governing 
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Published:
October 08, 2012
Author(s):
Cesar Ariel Pinto; Paul R. Garvey
Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise 
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Published:
July 20, 2012
Author(s):
Jana Jurečková; Pranab Sen; Jan Picek
Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from biomedical sciences to the public health disciplines, and, more recently, in genomics, bioinformatics, and financial statistics. These disciplines are presently 
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Published:
April 16, 2012
Author(s):
Ranjan Ganguli
This book provides a thorough understanding of the concepts of optimization methods from a modern perspective at the conceptual stage of complex technical systems. It focuses on nonlinear optimization with an emphasis on methods such as response surface and genetic algorithms. The text moves the 
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Published:
December 13, 2011
Author(s):
Ali Emrouznejad; William Ho
Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work. The book is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, 
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Published:
October 26, 2011
Author(s):
Wayne A. Woodward; Henry L. Gray; Alan Elliott
Virtually any random process developing chronologically can be viewed as a time series. In economics, closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series 
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Published:
August 26, 2011
Author(s):
Paul A. Tobias; David Trindade
Since the publication of the second edition of Applied Reliability in 1995, the ready availability of inexpensive, powerful statistical software has changed the way statisticians and engineers look at and analyze all kinds of data. Problems in reliability that were once difficult and time consuming 
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Published:
July 01, 2011
Author(s):
Jian Qing Shi; Taeryon Choi
Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed 
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Published:
May 18, 2011
Author(s):
Dieter Rasch; Jurgen Pilz; L.R. Verdooren; Albrecht Gebhardt
Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary 
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Published:
April 26, 2011
Author(s):
Bilal M. Ayyub; Richard H. McCuen
In a technological society, virtually every engineer and scientist needs to be able to collect, analyze, interpret, and properly use vast arrays of data. This means acquiring a solid foundation in the methods of data analysis and synthesis. Understanding the theoretical aspects is important, but 
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