Engineers commonly encounter problems that require them to make decisions under conditions of uncertainty. The uncertainty can be in the definition of the problem, the available information, the alternative solutions and their results, or the random nature of the solution outcomes. As engineers are required to solve increasingly complex design problems with limited resources, they must rely more and more on the proper treatment of uncertainty to make the best decisions. Probability, Statistics, and Reliability for Engineers will assist both engineering students and practicing engineers in understanding the fundamentals of probability, statistics, and reliability methods, especially their applications, limitations, and potentials.
Full of examples, this practical guide allows engineers to model very complex situations and predict an array of possible outcomes. It will also show readers how to write computational algorithms to solve probability and statistical problems.
Among the many examples cited are:
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