Skip to main content

Probability Concepts in Engineering: Emphasis on Applications to Civil and Environmental Engineering, 2nd Edition

Probability Concepts in Engineering: Emphasis on Applications to Civil and Environmental Engineering, 2nd Edition

Alfredo H-S. Ang, Wilson H. Tang

ISBN: 978-0-471-72064-5

Mar 2006

420 pages

Select type: Hardcover

In Stock



The material in the book is intended for a first course on applied probability and statistics for engineering students at the sophomore or junior level, or for self study, stressing probabilistic modeling and the fundamentals of statistical inferences. The primary aim is to provide an in-depth understanding of the fundamentals for the proper application in engineering problems.

The second edition of this well-known book (previously titled Probability Concepts in Engineering Planning and Design) by Alfredo Ang and Wilson Tang, two world-renowned educators, has been revised to simplify understanding the fundamentals of probability and statistics for engineering students. The second edition includes many new and expanded topics, including hypothesis testing and confidence intervals in regression analysis. Students using this text will develop the ability to formulate and solve real-world problems in engineering. The authors accomplish this by explaining all the concepts and methods through a variety of relevant engineering and physical problems.

  Each basic principle is presented and illustrated through different examples relevant to engineering and the physical sciences, particularly civil and environmental engineering.  The exercise problems in each chapter further enhance understanding of basic concepts and reinforce a working knowledge of concepts and methods. The authors firmly believe that the easiest and most effective way for engineers to learn and master a new set of abstract principles is to apply them to a variety of applications.

Related Resources

Chapter 1 -
Role of Probability and Statistics in Engineering
Chapter 2 -- Fundamentals of Probability Models
Chapter 3 -- Analytical Models of Random Phenomena
Chapter 4 -- Functions of Random Variables
Chapter 5 -
Computer-Based Numerical and Simulation Methods in Probability
Chapter 6 -- Statistical Inferences from Observational Data
Chapter 7 -- Determination of Probability Distribution Models
Chapter 8 -- Regression and Correlation Analyses
Chapter 9 -- The Bayesian Approach
Chapter 10 -
Elements of Quality Assurance and Acceptance Sampling
(Available only online at the Wiley web site)
Table A.1 -- Standard Normal Probabilities
Table A.2 -
CDF of the Binomial Distribution
Table A.3 -
Critical Values of t Distribution at Confidence Level (1- a)=p
Table A.4 -
Critical Values of the c2 Distribution at Confidence Level (1-a)=pTable A.5 -
Critical Values of Dna at Significance Level a in the K-S Test
Table A.6 -
Critical Values of the Anderson-Darling Goodness-of-fit Test
(for 4 specific distributions)
  • New illustrative examples and problems.
  • Distribution of extreme values, which are of special interest to engineers dealing with natural and extreme hazards (Chapter 3)
  • A new chapter, Chapter 5, has been added on Computer-Based Numerical and Simulation Methods in Probability.  
  • The Anderson-Darling method for goodness-of-fit test (Chapter 6)
  • Hypothesis Testing  (Chapter 6)
  • Linear regression has been expanded to include the determination of confidence intervals (Chapter 8)
  • Bayesian regression and correlation analyses (Chapter 9)
  • Chapter 10 on Quality Assurance and Acceptance Sampling, is now available exclusively on the book website.
  • Probabilistic modeling of engineering problems under uncertainty helps students understand probability models and formulate engineering problems containing uncertainty.

  • Illustrates the formulation and solution of engineering-type probabilistic problems through computer-based methods; including developing needed computer codes using commercial software such as MATLAB and MATHCAD.

  • Detailed examples and numerical illustrations help instructors explain the concept of aleatory and epistemic uncertainties.

  • Introduces and develops the analytical probabilistic models; also for formulating engineering problems under uncertainty.

  • Mathematical concepts are expounded through numerous numerical examples pertinent to engineering and the physical sciences.

  • Provides students a wide variety of examples to learn the specific mathematical concepts elucidated through each example problem.

  • A large number of exercise problems provide the instructor a wide variety of engineering-oriented problems to select for homework and examinations.

  • Although the illustrative examples and exercise problems pertain largely to civil and environmental engineering, the basic principles expounded in the book are equally applicable to other disciplines in engineering. Some of the examples and problems may also be pertinent, and equally easily understood by undergraduates, in these other disciplines.