000			02510cam a22001817a 4500
005			20250911093746.0
008			051212s2005 enka b 001 0 eng d
020			_a9788131211205
041			_aeng
082	0	4	_a519.2 _bIbeF
100	1		_aIbe, Oliver C.
245	1	0	_aFundamentals of Applied Probability and Random Processes / _cOliver C. Ibe.
260			_aBurlington, _aLondon : _bElsevier Academic Press; _c©2005
300			_axvii, 442 p.
520			_aKey Features Good and solid introduction to probability theory and stochastic processes Logically organized; writing is presented in a clear manner Choice of topics is comprehensive within the area of probability Ample homework problems are organized into chapter sections Description This book is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study. Readership Juniors and Seniors, but can also be used at lower graduate levels. Particularily welcome at engineering schools. Quotes "Each chapter is broken down into small subunits, making this a useful reference book as well as a textbook. The material is presented clearly, and solved problems are included in the text." --MAA Reviews Author Information By Oliver Ibe , University of Massachusetts, Lowell, U.S.A. Table of ContentsPreface Acknowledgments Chapter 1 Basic Probability Concepts 1.1 Introduction 1.2 Sample Space and Events 1.3 Definitions of Probability 1.3.1 Axiomatic Definition 1.3.2 Relative-Frequency Definition 1.3.3 Classical Definition 1.4 Applications of Probability 1.4.1 Reliability Engineering 1.4.2 Quality Control 1.4.3 Channel Noise 1.4.4 System Simulation 1.5 Elementary Set Theory 1.5.1 Set Operations 1.5.2 Number of Subsets of a Set 1.5.3 Venn Diagram 1.5.4 Set Identities 1.5.5 Duality Principle 1.6 Properties of Probability 1.7 Conditional Probability 1.7.1 Total Probability and the Bayes' Theorem 1.7.2 Tree Diagram 1.8 Independent Events 1.9 Combined Experiments 1.1
650		0	_aMathematics _xProbability
942			_cBK
999			_c948 _d948