Fundamentals of Systems Engineering with Economics, Probability, and Statistics

Fundamentals of Systems Engineering with Economics, Probability, and Statistics

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For one/two-semester, undergraduate/graduate-level courses in Systems Engineering in departments of Civil Engineering, Chemical, Electrical, Environmental, Mechanical, and Industrial Engineering, Urban Planning, Architecture, Construction Management.Based on the reality that today's engineers need a broad range of decision-making skills, this unique text 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 engineering students 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. Coverage is broad-based and applicable for students in practically all branches of engineering, not just civil engineering.show more

Product details

  • Hardback | 475 pages
  • 177.8 x 228.6 x 30.48mm | 771.1g
  • Pearson Education (US)
  • Pearson
  • United States
  • English
  • 0130106496
  • 9780130106490

Table of contents

(NOTE: Most chapters begin with an Introduction and conclude with Summary, References, and Exercises.)1. Mapping the Terrain of the Systems Approach. The Nature of Science. Engineering, Planning, Design, and Management. The Systems Approach. Steps in System Analysis. Classification of Systems. Systems Characteristics. Systems Analysis and Decision-Making. Models and Model-Building.2. Problem Solving and Designing in Engineering and Planning. Problem Solving and Designing. Hierarchy: Problem-Space, Trees, and Semi-Lattices. Problem Solving Styles. Wicked Problems. Measurement and Scaling. System Model Types and Model-Building. Problem-Solving through Group or Committee Action.3. Basic Engineering Economics & Evaluation. Notation. Simple Interest. Compound Interest. Uniform Series of Payments. Uniform Gradient Series. Discrete-Compound Interest Factors. Uniform Continuous Cash Flow and Capitalized Cost. Evaluation. Feasibility Issues. Evaluation Issues. The Evaluation Process. Values, Goals, Objectives, Criteria, and Standards. Estimation of Costs, Impacts, and Performance Levels. Evaluation of Alternatives. Economic and Financial Concepts. Analysis Techniques. Depreciation and Taxes. Reporting Results.4. Basic Microeconomics for Engineers and Planners. The Scope of Economics and Micro Economics. Some Basic Issues of Economics. Demand for Goods and Services. Demand, Supply, and Equilibrium. Sensitivity of Demand. Factors Affecting Elasticities. Kraft Demand Model. Direct and Cross Elasticities. Consumer Surplus. Costs. Consumer Choice.5. Principles of Probability: Part I-Review of Probability Theory. Events. Probability.6. Principles of Probability: Part II-Random Variables and Probability Distributions. Random Variables. Probability Functions. Describing Parameters of a Random Variable. Several Probability Functions.7. Principles of Probability: Part III-Joint Probability Functions and Correlated Variables. Joint Probability Functions. Covariance and Correlation. Functions of a Single Random Variable. Functions of Multiple Random Variables. Approximate Methods for Computing Mean, Variance, and Probability.8. Principles of Statistics: Part I-Estimation of Statistical Parameters and Testing Validity of Distribution Functions. Data Compression. Estimation of Mean and Variance. Confidence Intervals for Statistical Parameters. Estimation of Statistical Parameters Using the Method of Maximum Likelihood. Testing for a Desired Distribution Model.9. Principles of Statistics: Part II-Hypothesis Testing, Analysis of Variance, Regression and Correlation Analysis. Hypothesis Testing. Comparing Two Population Means. Analysis of Variance. Distribution Free Methods. Regression and Correlation Analysis.10. Basic Hard Systems Engineering-Part I. Introduction: Hard Systems Analysis? Methods Based on Calculus. Critical Path Method. Program Evaluation and Review Technique and the Line-of-Balance Techniques. Network Flow Analysis. Linear Programming.11. Basic Hard Systems Engineering-Part II. Forecasting. Transportation and Assignment Problem. Decision Analysis. Queuing Models. Simulation. Markov Analysis.12. Soft Systems Thinking and Analysis. What Is a System? A Preliminary Look. The Path from Optimization to Learning. Case Studies.Appendix A. Index.show more

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