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Based on the reality that today's engineers need a broad range of decision-making skills, this unique reference draws together--"into a single comprehensive volume"--all the fundamental principles of systems analysis (both hard and soft systems), economics (particularly microeconomics), probability, and statistics that engineers need to develop a rich, multifaceted perspective from which to tackle--and solve--complex engineering problems. The emphasis throughout is on presenting the fundamental concepts and their practical engineering applications, "unobscured by complicated mathematics." Using a large number of worked examples, it integrates the power of quantitative analysis with the conceptual richness of capital budgeting and microeconomics into the elements of systems engineering. Coverage is broad-based and applicable for engineers in practically "all" branches of engineering. The Systems Approach. Problem Solving in Engineering & Planning. Basic Engineering Economics & Evaluation. Basic Micro Economics for Engineers & Planners. Principles of Probability (Probability Theory; Random Variables and Probability Distributions; Joint Probability Functions and Correlated Variables). Principles of Statistics (Estimation of Statistical Parameters and Testing Validity of Distribution Functions; Hypothesis Testing, Analysis of Variance, Regression and Correlation Analysis). Basic Hard Systems Engineering. Basic Soft Systems Thinking & Analysis. For Civil, Chemical, Electrical, Environmental, Mechanical, and Industrial Engineers, Urban Planners, Architects, and Construction Managers.
This title offers an overview of the fundamentals and practice applications of probability and statistics, microeconomics, engineering economics, hard and soft systems analysis, and sustainable development and sustainability applications in engineering planning.
For first courses in probability, statistics, and decision theory for engineering students.
Engineering reliability concerns failure data analysis, the economics of maintenance policies, and system reliability. This textbook develops the use of probability and statistics in engineering reliability and maintenance problems. The author uses probability models in the analysis of failure data, decision relative to planned maintenance, and prediction relative to preliminary design.
Risk Analysis in Engineering and Economics is required reading for decision making under conditions of uncertainty. The author describes the fundamental concepts, techniques, and applications of the subject in a style tailored to meet the needs of students and practitioners of engineering, science, economics, and finance. Drawing on his extensive e
This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. This proven, accurate book and its excellent examples evidence Jay Devore’s reputation as an outstanding author and leader in the academic community. Devore emphasizes concepts, models, methodology, and applications as opposed to rigorous mathematical development and derivations. Through the use of lively and realistic examples, students go beyond simply learning about statistics-they actually put the methods to use. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Production Systems Engineering (PSE) is an emerging branch of Engineering intended to uncover fundamental principles of production systems and utilize them for analysis, continuous improvement, and design. This volume is the first ever textbook devoted exclusively to PSE. It is intended for senior undergraduate and first year graduate students interested in manufacturing. The development is first principle-based rather than recipe-based. The only prerequisite is elementary Probability Theory; however, all necessary probability facts are reviewed in an introductory chapter. Using a system-theoretic approach, this textbook provides analytical solutions for the following problems: mathematical modeling of production systems, performance analysis, constrained improvability, bottleneck identification and elimination, lean buffer design, product quality, customer demand satisfaction, transient behavior, and system-theoretic properties. Numerous case studies are presented. In addition, the so-called PSE Toolbox, which implements the algorithms developed, is described. The volume includes numerous case studies and problems for homework assignment.
This book presents the theory of probability and mathematical statistics at a level suitable for researchers at the frontiers of applied disciplines. Examples and exercises make essential concepts in measure theory and analysis accessible to those with preparation limited to vector calculus. Complete, detailed solutions to all the exercises demonstrate techniques of problem solving and provide immediate feedback.Part I, The Theory of Probability, starts with elementary set theory and proceeds through basic measure and probability, random variables, integration and mathematical expectation. It concludes with an extensive survey of models for distributions of random variables. Part II, The Theory of Statistics, begins with sampling theory and distribution theory for statistics from normal populations, proceeds to asymptotic (large-sample) theory, and on to point and interval estimation and tests of parametric hypotheses. The last three chapters cover tests of nonparametric hypotheses, Bayesian methods, and linear and nonlinear regression.Researchers and graduate students in applied fields such as actuarial science, biostatistics, economics, finance, mathematical psychology, and systems engineering will find this book to be a valuable learning tool and an essential reference.