Project Economics and Decision Analysis: Probabilistic models

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PennWell Books, 2002 - Business & Economics - 411 pages
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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
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Mian is a registered professional engineer in the State of Colorado.

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