Publication Date: March 3,2006 | ISBN-10: 047172064X ISBN-13 :978-0471720645 Edition: 2
Applied probability and statistics principles to practical engineering problems
The simplest, most effective way to learn the principles of probability models and statistical inference is applicable to various applications of these principles. That’s why Ang Lee and soup, the second edition of the works to explain the concept of probability (probability concepts in engineering planning and design) concepts and methods, using a wide range of issues, related to the engineering and physical sciences, in particular the Department of Civil and Environmental Engineering .
Now extensively revised, the new description of the problem, and new and expanded topics, this second edition will help you to develop a comprehensive understanding of probability and statistics capabilities, propose and solve real-world problems in engineering. The authors propose each basic principle using different examples, and give you the opportunity to improve your understanding and practical issues. Text ideal for students, as well as those who wish to adopt the principles and tools of self-learning and the use of statistics and probability.
In this second edition of the main features:
* A new chapter (Chapter 5), including computer-based numerical simulation methods in probability, extend and expand the analysis to more complex engineering problems.
* New and expanded coverage includes distribution of extreme values (Chapter 3), Anderson – Darling goodness goodness-of-fit test methods (Chapter 6) (Chapter 6), hypothesis testing, confidence intervals of linear regression OK (Chapter 8) and Bayesian regression and correlation analysis (Chapter 9).
* Many of the new movement in each chapter, to help you develop the concepts and methods of work experience.
* Provide a variety of examples, including many of the new version to help you learn and understand specific concepts.
* The probability of making and project type described by computer-based methods, including the development of the computer code of commercial software, such as MATLAB and Mathcad solution.
* The introduction and development of analytical probability model, and shows how to formulate engineering problems under conditions of uncertainty, and provide the fundamentals of quantitative risk assessment.
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