An integrated coverage of probability, statistics, Monte Carlo simulation, inferential statistics, design of experiments, systems reliability, fitting random data to models, analysis of variance, stochastic processes, and stochastic differential equations for engineers and scientists. The author for first time presents an introduction to the broad field of applied engineering uncertainty analysis in one comprehensive, friendly, coverage. Each concept is illustrated with several examples of relevance in engineering applications (no cards, colored balls, or dice): 478 pages; 177 solved examples; 147 proposed problems; 174 illustrations, 69 short computer programs; and 51 data and statistical tables. Clear presentation of concepts. Practical engineering examples. No cards, no dice, no colored balls. Prepares the reader for today's problems in engineering analysis, modeling, and design under uncertainty. This edition includes new research advances in nonlinear stochastic equations; simple methods to solve and graph boundary-value problems in several dimensions. Integrated treatment of probability, statistics, and stochastic modeling. Includes numerical (Monte Carlo) simulations and analytical modeling. Intuitive and graphical introduction to stochastic processes. Practical introduction to applied stochastic differential equations.