Cargando…

Risk, opportunity, uncertainty and other random models /

Risk, Opportunity, Uncertainty and Other Random Models (Volume V in the Working Guides to Estimating and Forecasting series) goes part way to debunking the myth that research and development cost are somewhat random, as under certain conditions they can be observed to follow a pattern of behaviour r...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Jones, Alan (Alan R.), 1953- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Abingdon, Oxon ; New York, NY : Routledge, 2019.
Colección:Working guides to estimating & forecasting.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

LEADER 00000cam a2200000 i 4500
001 OR_on1059521521
003 OCoLC
005 20231017213018.0
006 m o d
007 cr unu||||||||
008 181030s2019 enka ob 001 0 eng d
040 |a UMI  |b eng  |e rda  |e pn  |c UMI  |d TOH  |d OCLCF  |d K6U  |d OCLCO  |d TYFRS  |d OCLCQ  |d OCLCO  |d FAU  |d OCLCQ  |d OCLCO 
020 |a 9781315160030 
020 |a 131516003X 
020 |a 9781351661287 
020 |a 1351661280 
020 |z 9781138065055 
029 1 |a AU@  |b 000070335415 
035 |a (OCoLC)1059521521 
037 |a CL0501000002  |b Safari Books Online 
037 |a 9781315160030  |b Taylor & Francis 
050 4 |a TS167 
082 0 4 |a 338.5/1  |2 23 
049 |a UAMI 
100 1 |a Jones, Alan  |q (Alan R.),  |d 1953-  |e author. 
245 1 0 |a Risk, opportunity, uncertainty and other random models /  |c Alan R. Jones. 
264 1 |a Abingdon, Oxon ;  |a New York, NY :  |b Routledge,  |c 2019. 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Working guides to estimating & forecasting ;  |v volume 5 
588 0 |a Print version record. 
504 |a Includes bibliographical references and index. 
505 0 0 |t Foreword, 1 Introduction and Objectives, 1.1 Why write this book? Who might find it useful? Why Five Volumes?, 1.1.1 Why write this series? Who might find it useful?, 1.1.2 Why Five Volumes?, 1.2 Features you'll find in this book and others in this series, 1.2.1 Chapter Context, 1.2.2 The Lighter Side (humour), 1.2.3 Quotations, 1.2.4 Definitions, 1.2.5 Discussions and Explanations with a Mathematical Slant for Formula-philes, 1.2.6 Discussions and Explanations without a Mathematical Slant for Formula-phobes, 1.2.7 Caveat Augur, 1.2.8 Worked Examples, 1.2.9 Useful Microsoft Excel Functions and Facilities, 1.2.10 References to Authoritative Sources, 1.2.11 Chapter Reviews, 1.3 Overview of Chapters in this Volume, 1.4 Elsewhere in the 'Working Guide to Estimating & Forecasting' Series, 1.4.1 Volume I: Principles, Process and Practice of Professional Number Juggling, 1.4.2 Volume II: Probability, Statistics and other Frightening Stuff, 1.4.3 Volume III: Best Fit Lines & Curves, and some Mathe-Magical Transformations, 1.4.4 Volume IV: Learning, Unlearning and Re-Learning Curves, 1.4.5 Volume V: Risk, Opportunity, Uncertainty and Other Random Models, 1.5 Final Thoughts and Musings on this Volume and Series, References, , 2 Norden-Rayleigh Curves for Solution Development, 2.1 Norden-Rayleigh Curves: Who, What, Where, When and Why?, 2.1.1 Probability Density Function and Cumulative Distribution Function, 2.1.2 Truncation Options, 2.1.3 How does a Norden-Rayleigh Curve differ from the Rayleigh Distribution?, 2.1.4 Some Practical Limitations of the Norden-Rayleigh Curve, 2.2 Breaking the Norden-Rayleigh Rules, 2.2.1 Additional Objectives: Phased Development (or the Camelling), 2.2.2 Correcting an overly optimistic view of the problem complexity: The Square Rule, 2.2.3 Schedule Slippage due to Resource Ramp-up Delays: The Pro Rata Product Rule, 2.2.4 Schedule Slippage due to Premature Resource Reduction, 2.3 Beta Distribution: A Practical Alternative to Norden-Rayleigh, 2.3.1 PERT-Beta Distribution: a Viable Alternative to Norden-Rayleigh? 2.3.2 Resource Profiles with Norden-Rayleigh Curves and Beta Distribution PDFs, 2.4 Triangular Distribution: Another Alternative to Norden-Rayleigh, 2.5 Truncated Weibull Distributions and their Beta Equivalents, 2.5.1 Truncated Weibull Distributions for Solution Development, 2.5.2 General Beta Distributions for Solution Development, 2.6 Estimates to Completion with Norden-Rayleigh Curves, 2.6.1 Guess and Iterate Technique, 2.6.2 Norden-Rayleigh Curve Fitting with Microsoft Excel Solver, 2.6.3 Linear Transformation and Regression, 2.6.4 Exploiting Weibull Distribution's Double Log Linearisation Constraint, 2.6.5 Estimates to Completion -- Review and Conclusion, 2.7 Chapter Review, References, , 3 Monte Carlo Simulation and Other Random Thoughts, 3.1 Monte Carlo Simulation: Who, What, Why, Where, When and How, 3.1.1 Origins of Monte Carlo Simulation: Myth and Mirth, 3.1.2 Relevance to Estimators and Planners, 3.1.3 Key Principle: Input Variables with an Uncertain Future, 3.1.4 Common Pitfalls to Avoid, 3.1.5 Is our Monte Carlo Output Normal?, 3.1.6 Monte Carlo Simulation: A Model of Accurate Imprecision, 3.1.7 What if we don't know what the true Input Distribution Functions are?, 3.2 Monte Carlo Simulation and Correlation, 3.2.1 Independent Random Uncertain Events -- How Real is That?, 3.2.2 Modelling Semi-Independent Uncertain Events (Bees and Hedgehogs), 3.2.3 Chain-Linked Correlation Models, 3.2.4 Hub-Linked Correlation Models, 3.2.5 Using a Hub-Linked Model to Drive a Background Isometric Correlation, 3.2.6 Which Way Should We Go?, 3.2.7 A Word of Warning about Negative Correlation in Monte Carlo Simulation, 3.3 Modelling and Analysis of Risk Opportunity and Uncertainty, 3.3.1 Sorting the Wheat from the Chaff, 3.3.2 Modelling Risk Opportunity and Uncertainty in a Single Model, 3.3.3 Mitigating Risks, Realising Opportunities and Contingency Planning, 3.3.4 Getting our Risks, Opportunities and Uncertainties in a Tangle, 3.3.5 Dealing with High Probability Risks, 3.3.6 Beware of False Prophets: Dealing with Low Probability High Impact Risks, 3.3.7 Using Risk or Opportunity to Model Extreme Values of Uncertainty, 3.3.8 Modelling Probabilities of Occurrence, 3.3.9 Other Random Techniques for Evaluating Risk Opportunity and Uncertainty, 3.4 ROU Analysis: Choosing Appropriate Values with Confidence, 3.4.1 Monte Carlo Risk and Opportunity Analysis is Fundamentally Flawed!, 3.5 Chapter Review, References, , 4 Risk, Opportunity & Uncertainty: A Holistic Perspective, 4.1 Top-Down Approach to Risk Opportunity and Uncertainty, 4.1.1 Top-down Metrics, 4.1.2 Marching Army Technique: Cost-Schedule Related Variability, 4.1.3 Assumption Uplift Factors: Cost Variability Independent of Schedule Variability, 4.1.4 Lateral Shift Factors: Schedule Variability Independent of Cost Variability, 4.1.5 An Integrated Top-down Approach, 4.2 Bridging into the Unknown: Slipping and Sliding Technique, 4.3 Using an Estimate Maturity Assessment as a Guide to ROU Maturity, 4.4 Chapter Review, References, , 5 Factored Value Technique for Risks and Opportunities, 5.1 The Wrong Way, 5.2 A Slightly Better Way, 5.3 The Best Way, 5.4 Chapter Review, References, , 6 Introduction to Critical Path & Schedule Risk Analysis, 6.1 What is Critical Path Analysis?, 6.2 Finding a Critical Path Using Binary Activity Paths in Microsoft Excel, 6.3 Using Binary Paths to Find the Latest Start & Finish Times, and Float, 6.4 Using a Critical Path to Manage Cost and Schedule, 6.5 Modelling Variable Critical Paths Using Monte Carlo Simulation, 6.6 Chapter Review, References, , 7 Finally, After a Long Wait Queueing Theory, 7.1 Types of Queues and Service Discipline, 7.2 Memoryless Queues, 7.3 Simple Single Channel Queues (M/M/1 and M/G/1), 7.3.1 Example of Queueing Theory in Action M/M/1 or M/G/1, 7.4 Multiple Channel Queues (M/M/c), 7.4.1 Example of Queueing Theory in Action M/M/c or M/G/c, 7.5 How Do We Spot a Poisson Process?, 7.6 When is Weibull Viable?, 7.7 Can we have a Poisson Process with an Increasing / Decreasing Trend?, 7.8 Chapter Review, References, Epilogue, , Glossary of Estimating Terms, Index. 
520 3 |a Risk, Opportunity, Uncertainty and Other Random Models (Volume V in the Working Guides to Estimating and Forecasting series) goes part way to debunking the myth that research and development cost are somewhat random, as under certain conditions they can be observed to follow a pattern of behaviour referred to as a Norden-Rayleigh Curve, which unfortunately has to be truncated to stop the myth from becoming a reality! However, there is a practical alternative in relation to a particular form of PERT-Beta Curve. However, the major emphasis of this volume is the use of Monte Carlo Simulation as a general technique for narrowing down potential outcomes of multiple interacting variables or cost drivers. Perhaps the most common of these in the evaluation of Risk, Opportunity and Uncertainty. The trouble is that many Monte Carlo Simulation tools are 'black boxes' and too few estimators and forecasters really appreciate what is happening inside the 'black box'. This volume aims to resolve that and offers tips into things that might need to be considered to remove some of the uninformed random input that often creates a misinformed misconception of 'it must be right!'. Monte Carlo Simulation can be used to model variable determine Critical Paths in a schedule, and is key to modelling Waiting Times and cues with random arisings. Supported by a wealth of figures and tables, this is a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Costs, Industrial  |x Statistical methods. 
650 0 |a Research, Industrial  |x Statistical methods. 
650 0 |a Risk  |x Statistical methods. 
650 6 |a Coût de production  |x Méthodes statistiques. 
650 6 |a Recherche industrielle  |x Méthodes statistiques. 
650 6 |a Risque  |x Méthodes statistiques. 
650 7 |a Costs, Industrial  |x Statistical methods  |2 fast 
650 7 |a Research, Industrial  |x Statistical methods  |2 fast 
650 7 |a Risk  |x Statistical methods  |2 fast 
776 0 8 |i Print version:  |a Jones, Alan (Alan R.), 1953-  |t Risk, opportunity, uncertainty and other random models.  |d Abingdon, Oxon ; New York, NY : Routledge, 2018  |z 9781138065055  |w (DLC) 2017059096  |w (OCoLC)1022075457 
830 0 |a Working guides to estimating & forecasting. 
856 4 0 |u https://learning.oreilly.com/library/view/~/9781351661287/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
994 |a 92  |b IZTAP