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基本説明
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.
Full Description
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.
Contents
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)
Appendices:
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)
