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###-Book Description Begin-###
by Alfredo H-S. Ang (Author), Wilson H. Tang (Author)
Apply the principles of probability and statistics to realisticengineering problems
The easiest and most effective way to learn the principles ofprobabilistic modeling and statistical inference is to apply thoseprinciples to a variety of applications. That\'s why Ang and Tang\'sSecond Edition of Probability Concepts in Engineering (previouslytitled Probability Concepts in Engineering Planning and Design)explains concepts and methods using a wide range of problemsrelated to engineering and the physical sciences, particularlycivil and environmental engineering.
Now extensively revised with new illustrative problems and new andexpanded topics, this Second Edition will help you develop athorough understanding of probability and statistics and theability to formulate and solve real-world problems in engineering.The authors present each basic principle using different examples,and give you the opportunity to enhance your understanding withpractice problems. The text is ideally suited for students, as wellas those wishing to learn and apply the principles and tools ofstatistics and probability through self-study.
Key Features in this 2nd Edition:
* A new chapter (Chapter 5) covers Computer-Based Numerical andSimulation Methods in Probability, to extend and expand theanalytical methods to more complex engineering problems.
* New and expanded coverage includes distribution of extreme values(Chapter 3), the Anderson-Darling method for goodness-of-fit test(Chapter 6), hypothesis testing (Chapter 6), the determination ofconfidence intervals in linear regression (Chapter 8), and Bayesianregression and correlation analyses (Chapter 9).
* Many new exercise problems in each chapter help you develop aworking knowledge of concepts and methods.
* Provides a wide variety of examples, including many new to thisedition, to help you learn and understand specific concepts.
* Illustrates the formulation and solution of engineering-typeprobabilistic problems through computer-based methods, includingdeveloping computer codes using commercial software such as MATLABand MATHCAD.
* Introduces and develops analytical probabilistic models and showshow to formulate engineering problems under uncertainty, andprovides the fundamentals for quantitative risk assessment.
