Cost Estimation
Methods and Tools
1st Edition
Published on 19. June 2015
Book
Hardback
352 pages
978-1-118-53613-1 (ISBN)
Description
Presents an accessible approach to the cost estimation tools, concepts, and techniques needed to support analytical and cost decisions
Written with an easy-to-understand approach, Cost Estimation: Methods and Tools provides comprehensive coverage of the quantitative techniques needed by professional cost estimators and for those wanting to learn about this vibrant career field. Featuring the underlying mathematical and analytical principles of cost estimation, the book focuses on the tools and methods used to predict the research and development, production, and operating and support costs for successful cost estimation in industrial, business, and manufacturing processes.
The book begins with a detailed historical perspective and key terms of the cost estimating field in order to develop the necessary background prior to implementing the presented quantitative methods. The book proceeds to fundamental cost estimation methods utilized in the field of cost estimation, including working with inflation indices, regression analysis, learning curves, analogies, cost factors, and wrap rates. With a step-by-step introduction to the practicality of cost estimation and the available resources for obtaining relevant data, Cost Estimation: Methods and Tools also features:
Various cost estimating tools, concepts, and techniques needed to support business decisions
Multiple questions at the end of each chapter to help readers obtain a deeper understanding of the discussed methods and techniques
An overview of the software used in cost estimation, as well as an introduction to the application of risk and uncertainty analysis
A Foreword from Dr. Douglas A. Brook, a professor in the Graduate School of Business and Public Policy at the Naval Postgraduate School, who spent many years working in the Department of Defense acquisition environment
Cost Estimation: Methods and Tools is an excellent reference for academics and practitioners in decision science, operations research, operations management, business, and systems and industrial engineering, as well as a useful guide in support of professional cost estimation training and certification courses for practitioners. The book is also appropriate for graduate-level courses in operations research, operations management, engineering economics, and manufacturing and/or production processes.
Written with an easy-to-understand approach, Cost Estimation: Methods and Tools provides comprehensive coverage of the quantitative techniques needed by professional cost estimators and for those wanting to learn about this vibrant career field. Featuring the underlying mathematical and analytical principles of cost estimation, the book focuses on the tools and methods used to predict the research and development, production, and operating and support costs for successful cost estimation in industrial, business, and manufacturing processes.
The book begins with a detailed historical perspective and key terms of the cost estimating field in order to develop the necessary background prior to implementing the presented quantitative methods. The book proceeds to fundamental cost estimation methods utilized in the field of cost estimation, including working with inflation indices, regression analysis, learning curves, analogies, cost factors, and wrap rates. With a step-by-step introduction to the practicality of cost estimation and the available resources for obtaining relevant data, Cost Estimation: Methods and Tools also features:
Various cost estimating tools, concepts, and techniques needed to support business decisions
Multiple questions at the end of each chapter to help readers obtain a deeper understanding of the discussed methods and techniques
An overview of the software used in cost estimation, as well as an introduction to the application of risk and uncertainty analysis
A Foreword from Dr. Douglas A. Brook, a professor in the Graduate School of Business and Public Policy at the Naval Postgraduate School, who spent many years working in the Department of Defense acquisition environment
Cost Estimation: Methods and Tools is an excellent reference for academics and practitioners in decision science, operations research, operations management, business, and systems and industrial engineering, as well as a useful guide in support of professional cost estimation training and certification courses for practitioners. The book is also appropriate for graduate-level courses in operations research, operations management, engineering economics, and manufacturing and/or production processes.
Reviews / Votes
"This book is a manual of how to effectively internally manage a company, and maximise operational external efficiency of a contractor. On this basis it is essential reading for anyone in a decision-taking role, even if only a relatively minor role in bringing productions to market." (Chromatographia 2016)More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 23 mm
Weight
686 gr
ISBN-13
978-1-118-53613-1 (9781118536131)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Book
04/2026
2nd Edition
Wiley
€115.50
Shipment within 15-20 days
Additional editions
E-Book
05/2015
Wiley
€106.99
Available for download
E-Book
04/2015
Wiley
€106.99
Available for download
Persons
Gregory K. Mislick is Senior Lecturer in the Department of Operations Research and Program Manager for the Masters Degree Program in Cost Estimating and Analysis at the Naval Postgraduate School (NPS). A retired U.S. Marine Corps Lieutenant Colonel aviator and past associate dean of the Graduate School of Operational and Information Sciences at NPS, his research interests includes life cycle cost estimating and modeling, probability and statistics, regression analysis, learning curves, and optimization.
Daniel A. Nussbaum, PhD, is Visiting Professor in the Department of Operations Research at the Naval Postgraduate School in Monterey, California. With over 30 years of professional experience providing financial estimating and analysis services to senior levels of the U.S. Federal government, Dr. Nussbaum's research interests includes cost/benefit analyses, life cycle cost estimating and modeling, and financial modeling.
Daniel A. Nussbaum, PhD, is Visiting Professor in the Department of Operations Research at the Naval Postgraduate School in Monterey, California. With over 30 years of professional experience providing financial estimating and analysis services to senior levels of the U.S. Federal government, Dr. Nussbaum's research interests includes cost/benefit analyses, life cycle cost estimating and modeling, and financial modeling.
Content
Foreword xiii
About the Authors xvii
Preface xix
Acronyms xxiii
1 "Looking Back: Reflections on Cost Estimating" 1
Reference 10
2 Introduction to Cost Estimating 11
2.1 Introduction 11
2.2 What is Cost Estimating? 11
2.3 What Are the Characteristics of a Good Cost Estimate? 13
2.4 Importance of Cost Estimating in DoD and in Congress. Why Do We Do Cost Estimating? 14
2.4.1 Importance of Cost Estimating to Congress 16
2.5 An Overview of the DoD Acquisition Process 17
2.6 Acquisition Categories (ACATs) 23
2.7 Cost Estimating Terminology 24
Summary 30
References 31
Applications and Questions 31
3 Non-DoD Acquisition and the Cost Estimating Process 32
3.1 Introduction 32
3.2 Who Practices Cost Estimation? 32
3.3 The Government Accountability Office (GAO) and the 12-Step Process 33
3.4 Cost Estimating in Other Non-DoD Agencies and Organizations 38
3.4.1 The Intelligence Community (IC) 38
3.4.2 National Aeronautics and Space Administration (NASA) 38
3.4.3 The Federal Aviation Administration (FAA) 39
3.4.4 Commercial Firms 39
3.4.5 Cost Estimating Book of Knowledge (CEBOK) 40
3.4.6 Federally Funded Research and Development Centers (FFRDCs) 41
3.4.7 The Institute for Defense Analysis (IDA) 41
3.4.8 The Mitre Corporation 42
3.4.9 Rand Corporation 42
3.5 The Cost Estimating Process 43
3.6 Definition and Planning. Knowing the Purpose of the Estimate 43
3.6.1 Definition and Planning. Defining the System 47
3.6.2 Definition and Planning. Establishing the Ground Rules and Assumptions 48
3.6.3 Definition and Planning. Selecting the Estimating Approach 49
3.6.4 Definition and Planning. Putting the Team Together 51
3.7 Data Collection 52
3.8 Formulation of the Estimate 52
3.9 Review and Documentation 53
3.10 Work Breakdown Structure (WBS) 53
3.10.1 Program Work Breakdown Structure 53
3.10.2 Military-Standard (MIL-STD) 881C 56
3.11 Cost Element Structure (CES) 56
Summary 58
References 59
Applications and Questions 59
4 Data Sources 61
4.1 Introduction 61
4.2 Background and Considerations to Data Collection 61
4.2.1 Cost Data 63
4.2.2 Technical Data 63
4.2.3 Programmatic Data 64
4.2.4 Risk Data 64
4.3 Cost Reports and Earned Value Management (EVM) 65
4.3.1 Contractor Cost Data Reporting (CCDR) 65
4.3.2 Contract Performance Report (CPR) 66
4.3.3 EVM Example 70
4.4 Cost Databases 74
4.4.1 Defense Cost and Resource Center (DCARC) 75
4.4.2 Operating and Support Costs Databases 75
4.4.3 Defense Acquisition Management Information Retrieval (DAMIR) 76
Summary 76
Reference 77
Applications and Questions 77
5 Data Normalization 78
5.1 Introduction 78
5.2 Background to Data Normalization 78
5.3 Normalizing for Content 80
5.4 Normalizing for Quantity 81
5.5 Normalizing for Inflation 83
5.6 DoD Appropriations and Background 87
5.7 Constant Year Dollars (CY$) 88
5.8 Base Year Dollars (BY$) 90
5.9 DoD Inflation Indices 91
5.10 Then Year Dollars (TY$) 95
5.11 Using the Joint Inflation Calculator (JIC) 97
5.12 Expenditure (Outlay) Profile 99
Summary 103
References 103
Applications and Questions 103
6 Statistics for Cost Estimators 105
6.1 Introduction 105
6.2 Background to Statistics 105
6.3 Margin of Error 106
6.4 Taking a Sample 109
6.5 Measures of Central Tendency 110
6.6 Dispersion Statistics 113
6.7 Coefficient of Variation 117
Summary 119
References 119
General Reference 119
Applications and Questions 119
7 Linear Regression Analysis 121
7.1 Introduction 121
7.2 Home Buying Example 121
7.3 Regression Background and Nomenclature 126
7.4 Evaluating a Regression 132
7.5 Standard Error (SE) 133
7.6 Coefficient of Variation (CV) 134
7.7 Analysis of Variance (ANOVA) 135
7.8 Coefficient of Determination (R2) 137
7.9 F-Statistic and t-Statistics 138
7.10 Regression Hierarchy 140
7.11 Staying Within the Range of Your Data 142
7.12 Treatment of Outliers 143
7.12.1 Handling Outliers with Respect to X (The Independent Variable Data) 143
7.12.2 Handling Outliers with Respect to Y (The Dependent Variable Data) 144
7.13 Residual Analysis 146
7.14 Assumptions of Ordinary Least Squares (OLS) Regression 149
Summary 149
Reference 150
Applications and Questions 150
8 Multi-Variable Linear Regression Analysis 152
8.1 Introduction 152
8.2 Background of Multi-Variable Linear Regression 152
8.3 Home Prices 154
8.4 Multi-Collinearity (MC) 158
8.5 Detecting Multi-Collinearity (MC) Method #1: Widely Varying Regression Slope Coefficients 159
8.6 Detecting Multi-Collinearity Method #2: Correlation Matrix 160
8.7 Multi-Collinearity Example #1: Home Prices 161
8.8 Determining Statistical Relationships between Independent Variables 163
8.9 Multi-Collinearity Example #2: Weapon Systems 164
8.10 Conclusions of Multi-Collinearity 167
8.11 Multi-Variable Regression Guidelines 168
Summary 169
Applications and Questions 170
9 Intrinsically Linear Regression 172
9.1 Introduction 172
9.2 Background of Intrinsically Linear Regression 172
9.3 The Multiplicative Model 173
9.4 Data Transformation 174
9.5 Interpreting the Regression Results 178
Summary 178
Reference 179
Applications and Questions 179
10 Learning Curves: Unit Theory 180
10.1 Introduction 180
10.2 Learning Curve Scenario #1 180
10.3 Cumulative AverageTheory Overview 182
10.4 UnitTheory Overview 182
10.5 UnitTheory 185
10.6 Estimating Lot Costs 188
10.7 Fitting a Curve Using Lot Data 191
10.7.1 Lot Midpoint 192
10.7.2 Average Unit Cost (AUC) 194
10.8 UnitTheory Final Example (Example 10.5) 197
10.9 Alternative LMP and Lot Cost Calculations 200
Summary 202
References 202
Applications and Questions 202
11 Learning Curves: Cumulative Average Theory 204
11.1 Introduction 204
11.2 Background of Cumulative AverageTheory (CAT) 204
11.3 Cumulative AverageTheory 206
11.4 Estimating Lot Costs 210
11.5 Cumulative AverageTheory Final Example 210
11.6 UnitTheory vs. Cumulative AverageTheory 214
11.6.1 Learning Curve Selection 215
Summary 216
Applications and Questions 216
12 Learning Curves: Production Breaks/Lost Learning 218
12.1 Introduction 218
12.2 The Lost Learning Process 219
12.3 Production Break Scenario 219
12.4 The Anderlohr Method 220
12.5 Production Breaks Example 221
12.6 The Retrograde Method Example 12.1 (Part 2) 224
Summary 229
References 229
Applications and Questions 230
13 Wrap Rates and Step-Down Functions 231
13.1 Introduction 231
13.2 Wrap Rate Overview 231
13.3 Wrap Rate Components 232
13.3.1 Direct Labor Rate 233
13.3.2 Overhead Rate 233
13.3.3 Other Costs 234
13.4 Wrap Rate Final Example (Example 13.2) 235
13.5 Summary of Wrap Rates 236
13.6 Introduction to Step-Down Functions 236
13.7 Step-Down Function Theory 237
13.8 Step-Down Function Example 13.1 238
13.9 Summary of Step-Down Functions 240
Reference 240
Applications and Questions 240
14 Cost Factors and the Analogy Technique 242
14.1 Introduction 242
14.2 Cost Factors Scenario 242
14.3 Cost Factors 243
14.4 Which Factor to Use? 246
14.5 Cost Factors Handbooks 246
14.6 Unified Facilities Criteria (UFC) 247
14.7 Summary of Cost Factors 248
14.8 Introduction to the Analogy Technique 248
14.9 Background of Analogy 249
14.10 Methodology 250
14.11 Example 14.1 Part 1: The Historical WBS 250
14.12 Example 14.1 Part 2: The New WBS 253
14.13 Summary of the Analogy Technique 255
Reference 256
Applications and Questions 256
15 Software Cost Estimation 257
15.1 Introduction 257
15.2 Background on Software Cost Estimation 257
15.3 What is Software? 258
15.4 The WBS Elements in a typical Software Cost Estimating Task 259
15.5 Software Costing Characteristics and Concerns 260
15.6 Measuring Software Size: Source Lines of Code (SLOC) and Function Points (FP) 261
15.6.1 Source Lines of Code: (SLOC) 261
15.6.2 Function Point (FP) Analysis 263
15.7 The Software Cost Estimating Process 264
15.8 Problems with Software Cost Estimating: Cost Growth 265
15.9 Commercial Software Availability 267
15.9.1 COTS in the Software Environment 268
15.10 Post Development Software Maintenance Costs 268
Summary 269
References 269
16 Cost Benefit Analysis and Risk and Uncertainty 270
16.1 Introduction 270
16.2 Cost Benefit Analysis (CBA) and Net Present Value (NPV) Overview 270
16.3 Time Value of Money 273
16.4 Example 16.1. Net Present Value 277
16.5 Risk and Uncertainty Overview 281
16.6 Considerations for Handling Risk and Uncertainty 283
16.7 How do the Uncertainties Affect our Estimate? 284
16.8 Cumulative Cost and Monte Carlo Simulation 287
16.9 Suggested Resources on Risk and Uncertainty Analysis 289
Summary 290
References 290
Applications and Questions 290
17 Epilogue: The Field of Cost Estimating and Analysis 291
Answers to Questions 295
Index 309
About the Authors xvii
Preface xix
Acronyms xxiii
1 "Looking Back: Reflections on Cost Estimating" 1
Reference 10
2 Introduction to Cost Estimating 11
2.1 Introduction 11
2.2 What is Cost Estimating? 11
2.3 What Are the Characteristics of a Good Cost Estimate? 13
2.4 Importance of Cost Estimating in DoD and in Congress. Why Do We Do Cost Estimating? 14
2.4.1 Importance of Cost Estimating to Congress 16
2.5 An Overview of the DoD Acquisition Process 17
2.6 Acquisition Categories (ACATs) 23
2.7 Cost Estimating Terminology 24
Summary 30
References 31
Applications and Questions 31
3 Non-DoD Acquisition and the Cost Estimating Process 32
3.1 Introduction 32
3.2 Who Practices Cost Estimation? 32
3.3 The Government Accountability Office (GAO) and the 12-Step Process 33
3.4 Cost Estimating in Other Non-DoD Agencies and Organizations 38
3.4.1 The Intelligence Community (IC) 38
3.4.2 National Aeronautics and Space Administration (NASA) 38
3.4.3 The Federal Aviation Administration (FAA) 39
3.4.4 Commercial Firms 39
3.4.5 Cost Estimating Book of Knowledge (CEBOK) 40
3.4.6 Federally Funded Research and Development Centers (FFRDCs) 41
3.4.7 The Institute for Defense Analysis (IDA) 41
3.4.8 The Mitre Corporation 42
3.4.9 Rand Corporation 42
3.5 The Cost Estimating Process 43
3.6 Definition and Planning. Knowing the Purpose of the Estimate 43
3.6.1 Definition and Planning. Defining the System 47
3.6.2 Definition and Planning. Establishing the Ground Rules and Assumptions 48
3.6.3 Definition and Planning. Selecting the Estimating Approach 49
3.6.4 Definition and Planning. Putting the Team Together 51
3.7 Data Collection 52
3.8 Formulation of the Estimate 52
3.9 Review and Documentation 53
3.10 Work Breakdown Structure (WBS) 53
3.10.1 Program Work Breakdown Structure 53
3.10.2 Military-Standard (MIL-STD) 881C 56
3.11 Cost Element Structure (CES) 56
Summary 58
References 59
Applications and Questions 59
4 Data Sources 61
4.1 Introduction 61
4.2 Background and Considerations to Data Collection 61
4.2.1 Cost Data 63
4.2.2 Technical Data 63
4.2.3 Programmatic Data 64
4.2.4 Risk Data 64
4.3 Cost Reports and Earned Value Management (EVM) 65
4.3.1 Contractor Cost Data Reporting (CCDR) 65
4.3.2 Contract Performance Report (CPR) 66
4.3.3 EVM Example 70
4.4 Cost Databases 74
4.4.1 Defense Cost and Resource Center (DCARC) 75
4.4.2 Operating and Support Costs Databases 75
4.4.3 Defense Acquisition Management Information Retrieval (DAMIR) 76
Summary 76
Reference 77
Applications and Questions 77
5 Data Normalization 78
5.1 Introduction 78
5.2 Background to Data Normalization 78
5.3 Normalizing for Content 80
5.4 Normalizing for Quantity 81
5.5 Normalizing for Inflation 83
5.6 DoD Appropriations and Background 87
5.7 Constant Year Dollars (CY$) 88
5.8 Base Year Dollars (BY$) 90
5.9 DoD Inflation Indices 91
5.10 Then Year Dollars (TY$) 95
5.11 Using the Joint Inflation Calculator (JIC) 97
5.12 Expenditure (Outlay) Profile 99
Summary 103
References 103
Applications and Questions 103
6 Statistics for Cost Estimators 105
6.1 Introduction 105
6.2 Background to Statistics 105
6.3 Margin of Error 106
6.4 Taking a Sample 109
6.5 Measures of Central Tendency 110
6.6 Dispersion Statistics 113
6.7 Coefficient of Variation 117
Summary 119
References 119
General Reference 119
Applications and Questions 119
7 Linear Regression Analysis 121
7.1 Introduction 121
7.2 Home Buying Example 121
7.3 Regression Background and Nomenclature 126
7.4 Evaluating a Regression 132
7.5 Standard Error (SE) 133
7.6 Coefficient of Variation (CV) 134
7.7 Analysis of Variance (ANOVA) 135
7.8 Coefficient of Determination (R2) 137
7.9 F-Statistic and t-Statistics 138
7.10 Regression Hierarchy 140
7.11 Staying Within the Range of Your Data 142
7.12 Treatment of Outliers 143
7.12.1 Handling Outliers with Respect to X (The Independent Variable Data) 143
7.12.2 Handling Outliers with Respect to Y (The Dependent Variable Data) 144
7.13 Residual Analysis 146
7.14 Assumptions of Ordinary Least Squares (OLS) Regression 149
Summary 149
Reference 150
Applications and Questions 150
8 Multi-Variable Linear Regression Analysis 152
8.1 Introduction 152
8.2 Background of Multi-Variable Linear Regression 152
8.3 Home Prices 154
8.4 Multi-Collinearity (MC) 158
8.5 Detecting Multi-Collinearity (MC) Method #1: Widely Varying Regression Slope Coefficients 159
8.6 Detecting Multi-Collinearity Method #2: Correlation Matrix 160
8.7 Multi-Collinearity Example #1: Home Prices 161
8.8 Determining Statistical Relationships between Independent Variables 163
8.9 Multi-Collinearity Example #2: Weapon Systems 164
8.10 Conclusions of Multi-Collinearity 167
8.11 Multi-Variable Regression Guidelines 168
Summary 169
Applications and Questions 170
9 Intrinsically Linear Regression 172
9.1 Introduction 172
9.2 Background of Intrinsically Linear Regression 172
9.3 The Multiplicative Model 173
9.4 Data Transformation 174
9.5 Interpreting the Regression Results 178
Summary 178
Reference 179
Applications and Questions 179
10 Learning Curves: Unit Theory 180
10.1 Introduction 180
10.2 Learning Curve Scenario #1 180
10.3 Cumulative AverageTheory Overview 182
10.4 UnitTheory Overview 182
10.5 UnitTheory 185
10.6 Estimating Lot Costs 188
10.7 Fitting a Curve Using Lot Data 191
10.7.1 Lot Midpoint 192
10.7.2 Average Unit Cost (AUC) 194
10.8 UnitTheory Final Example (Example 10.5) 197
10.9 Alternative LMP and Lot Cost Calculations 200
Summary 202
References 202
Applications and Questions 202
11 Learning Curves: Cumulative Average Theory 204
11.1 Introduction 204
11.2 Background of Cumulative AverageTheory (CAT) 204
11.3 Cumulative AverageTheory 206
11.4 Estimating Lot Costs 210
11.5 Cumulative AverageTheory Final Example 210
11.6 UnitTheory vs. Cumulative AverageTheory 214
11.6.1 Learning Curve Selection 215
Summary 216
Applications and Questions 216
12 Learning Curves: Production Breaks/Lost Learning 218
12.1 Introduction 218
12.2 The Lost Learning Process 219
12.3 Production Break Scenario 219
12.4 The Anderlohr Method 220
12.5 Production Breaks Example 221
12.6 The Retrograde Method Example 12.1 (Part 2) 224
Summary 229
References 229
Applications and Questions 230
13 Wrap Rates and Step-Down Functions 231
13.1 Introduction 231
13.2 Wrap Rate Overview 231
13.3 Wrap Rate Components 232
13.3.1 Direct Labor Rate 233
13.3.2 Overhead Rate 233
13.3.3 Other Costs 234
13.4 Wrap Rate Final Example (Example 13.2) 235
13.5 Summary of Wrap Rates 236
13.6 Introduction to Step-Down Functions 236
13.7 Step-Down Function Theory 237
13.8 Step-Down Function Example 13.1 238
13.9 Summary of Step-Down Functions 240
Reference 240
Applications and Questions 240
14 Cost Factors and the Analogy Technique 242
14.1 Introduction 242
14.2 Cost Factors Scenario 242
14.3 Cost Factors 243
14.4 Which Factor to Use? 246
14.5 Cost Factors Handbooks 246
14.6 Unified Facilities Criteria (UFC) 247
14.7 Summary of Cost Factors 248
14.8 Introduction to the Analogy Technique 248
14.9 Background of Analogy 249
14.10 Methodology 250
14.11 Example 14.1 Part 1: The Historical WBS 250
14.12 Example 14.1 Part 2: The New WBS 253
14.13 Summary of the Analogy Technique 255
Reference 256
Applications and Questions 256
15 Software Cost Estimation 257
15.1 Introduction 257
15.2 Background on Software Cost Estimation 257
15.3 What is Software? 258
15.4 The WBS Elements in a typical Software Cost Estimating Task 259
15.5 Software Costing Characteristics and Concerns 260
15.6 Measuring Software Size: Source Lines of Code (SLOC) and Function Points (FP) 261
15.6.1 Source Lines of Code: (SLOC) 261
15.6.2 Function Point (FP) Analysis 263
15.7 The Software Cost Estimating Process 264
15.8 Problems with Software Cost Estimating: Cost Growth 265
15.9 Commercial Software Availability 267
15.9.1 COTS in the Software Environment 268
15.10 Post Development Software Maintenance Costs 268
Summary 269
References 269
16 Cost Benefit Analysis and Risk and Uncertainty 270
16.1 Introduction 270
16.2 Cost Benefit Analysis (CBA) and Net Present Value (NPV) Overview 270
16.3 Time Value of Money 273
16.4 Example 16.1. Net Present Value 277
16.5 Risk and Uncertainty Overview 281
16.6 Considerations for Handling Risk and Uncertainty 283
16.7 How do the Uncertainties Affect our Estimate? 284
16.8 Cumulative Cost and Monte Carlo Simulation 287
16.9 Suggested Resources on Risk and Uncertainty Analysis 289
Summary 290
References 290
Applications and Questions 290
17 Epilogue: The Field of Cost Estimating and Analysis 291
Answers to Questions 295
Index 309