# Project Economics and Decision Analysis: Probabilistic models

PennWell Books, 2002 - Business & Economics - 411 pages
This comprehensive two-volume set provides all the necessary concepts of capital investment evaluation, capital budgeting, & decision analysis.

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### Contents

 INTRODUCTION 1 Handling Uncertainty in Capital Investments 4 Industry Practice Over the Years 6 Classification of Decision Situations 7 Terminology Used in Decision Analysis 8 The Decision Analysis Cycle 11 Advantages of Decision Analysis 16 Misconceptions Regarding Decision Analysis 17
 Expected Value of Imperfect Information EVII 190 Decision Trees 197 Decision Tree Convention 198 Guidelines for Designing Trees 200 Solving a Decision Tree 201 Constructing Risk Profiles 207 Advantages of Decision Trees 208 Spreadsheet Applications 209

 Applications of Decision Analysis 19 Typical Industry Risks 20 Questions and Problems 24 STATISTICS AND PROBABILITY CONCEPTS 27 Descriptive Statistics 28 Measures of Central Tendency 30 Mean Median and Mode 31 Geometric Harmonic and Quadratic Mean 35 Weighted Average 39 Choice of a Suitable Average 42 Measures of Variability 44 Range Variance and Standard Deviation 45 Mean Absolute Deviation 46 Coefficient of Variation 47 Descriptive Statistics from Grouped Data 50 Mean Median and Mode 52 Geometric and Harmonic Mean 53 Graphical Presentation of Data 56 Other Measures 62 Dociles and Percentiles 64 Coefficient of Peakedness and Skewness 66 Understanding Probability Concepts 70 Objective Probability 72 Empirical Approach 75 Subjective Probability 77 Operations on Event Sets 81 Characteristics of Events 82 Rules of Probability 84 Complementation Rule 85 Multiplication Rule 87 Probability Table and Probability Tree 92 Bayes Rule 94 Theoretical Probability Distributions 99 Discrete Probability Distributions 101 Multinomial Probability Distribution 105 Hypergeometric Probability Distribution 107 Poisson Probability Distribution 110 Continuous Probability Distributions 113 Normal Probability Distribution 114 Lognormal Probability Distribution 122 Uniform Probability Distribution 126 Triangular Probability Distribution 128 Spreadsheet Application 132 Introducing BestFit 138 BestFit Addin 139 Questions and Problems 142 EXPECTED VALUE AND DECISION TREES 151 Expected Value Concepts 153 Expected Value of Random Variable 154 Standard Deviation of Random Variable 155 Expected Monetary Value EMV 157 Sensitivity Analysis 163 Expected Profitability Index EPI 166 Performance Index 172 MeanVariance and Stochastic Dominance 174 Meaning and Interpretation of Expected Value 181 Characteristics of Expected Value 185 Value of Information 186 Expected Value of Perfect Information EVPI 187
 Introducing PrecisionTree 210 Constructing the Tree 213 Risk Profile 219 Sensitivity Analysis 220 Questions and Problems 227 INCORPORATING ATTITUDES TOWARD RISK 235 The Expected Utility Theory 237 The Axioms of Utility 241 Risk Tolerance 244 Certainty Equivalent and Risk Premium 246 Assessing the Utility Function 250 Mathematical Representation of Utility Functions 255 Approximation to Certainty Equivalent 262 Risk Aversion 263 Expected Utility Decision Criteria 268 Spreadsheet Applications 269 Finding the Certainty Equivalent 273 Critical Risk Tolerance 274 PrecisionTree and Utility Functions 276 Questions and Problems 280 Determining Venture Participation 285 Gamblers Ruin 287 Working Interest and RAY 289 Optimum Working Interest 290 Breakeven Working Interest 291 Based on Hyperbolic Risk Aversion 293 Parabolic Approximation to Cozzolinos RAV 298 Modified RiskAdjusted Value 300 Portfolio Balancing and RAV 303 Portfolio BalancingCozzolino RAV Formula 304 Portfolio BalancingParabolic RAV Formula 305 Spreadsheet Applications 307 SIMULATION IN DECISION ANALYSIS 311 Designing the Simulation Model 314 Real Applications of Simulation 315 Steps in Simulation Modeling 316 Random Sampling Methods 322 Monte Carlo Sampling 324 Latin Hypercube Sampling 326 BehindTheScene Calculations 328 Recognizing Dependence on Input Variables 333 Simulating Total Dependence 338 Simulating Diffuse Dependence 339 Spreadsheet Applications 347 Using Excel for Simulation 348 Probability Distributions in Excel 349 Introducing RISK 352 Loading RISK 354 Developing the Simulation Model 355 Running the Simulation 359 Analyzing the Output 361 Handling Dependency on RISK 370 Combining PrescisionTree and RISK 373 Afterword 379 Probability Tables 383 Contents of the Accompanying CDROM 395 Index 399 Copyright