List of Figures |
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xiii | |
List of Tables |
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xvii | |
Foreword |
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xxii | |
1 Introduction and objectives |
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1 | (13) |
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1.1 Why write this book? Who might find it useful? Why five volumes? |
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1.1.1 Why write this series? Who might find it useful? |
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2 | (1) |
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1.2 Features you'll find in this book and others in this series |
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3 | (1) |
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1.2.2 The lighter side (humour) |
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3 | (1) |
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1.2.5 Discussions and explanations with a mathematical slant for Formula-philes |
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4 | (1) |
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1.2.6 Discussions and explanations without a mathematical slant for Formula-phobes |
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5 | (1) |
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6 | (1) |
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1.2.9 Useful Microsoft Excel functions and facilities |
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6 | (1) |
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1.2.10 References to authoritative sources |
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6 | (1) |
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7 | (1) |
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1.3 Overview of chapters in this volume |
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7 | (1) |
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1.4 Elsewhere in the 'Working Guide to Estimating & Forecasting' series |
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8 | (4) |
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1.4.1 Volume I: Principles, Process and Practice of Professional Number Juggling |
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9 | (1) |
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1.4.2 Volume II: Probability, Statistics and Other Frightening Stuff |
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9 | (1) |
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1.4.3 Volume III: Best Fit Lines and Curves, and Some Mathe-Magical Transformations |
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10 | (1) |
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1.4.4 Volume IV: Learning, Unlearning and Re-Learning Curves |
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11 | (1) |
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1.4.5 Volume V: Risk, Opportunity, Uncertainty and Other Random Models |
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11 | (1) |
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1.5 Final thoughts and musings on this volume and series |
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12 | (1) |
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13 | (1) |
2 Quantity-based Learning Curves |
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14 | (85) |
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2.1 A brief history of the Learning Curve as a formal relationship |
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16 | (1) |
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2.2 Two basic Learning Curve models (Wright and Crawford) |
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17 | (22) |
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2.2.1 Wright Cumulative Average Learning Curve |
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18 | (5) |
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2.2.2 Crawford Unit Learning Curve |
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23 | (3) |
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2.2.3 Wright and Crawford Learning Curves compared |
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26 | (1) |
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2.2.4 What's so special about the doubling rule? |
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27 | (6) |
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2.2.5 Learning Curve regression -What appears to be Wright, may in fact be wrong! |
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33 | (6) |
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2.3 Variations on the basic Learning Curve models |
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39 | (12) |
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2.3.1 DeJong Unit Learning Curve |
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39 | (1) |
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2.3.2 DeJong-Wright Cumulative Average Hybrid Learning Curve |
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40 | (3) |
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2.3.3 Stanford-B Unit Learning Curve |
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43 | (2) |
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2.3.4 Stanford-Wright Cumulative Average Hybrid Learning Curve |
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45 | (2) |
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2.3.5 S-Curve Unit Learning Curve |
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47 | (1) |
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2.3.6 S-Curve-Wright Cumulative Average Hybrid Learning Curve |
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48 | (3) |
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2.4 Where and when to apply learning and how much? |
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51 | (16) |
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2.4.1 To what kind of task can a Learning Curve be applied? |
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51 | (3) |
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2.4.2 Additive and non-additive properties of Learning Curves |
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54 | (2) |
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2.4.3 Calibrating or measuring observed learning |
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56 | (6) |
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2.4.4 What if we don't have any actuals? Rules of Thumb rates of learning |
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62 | (5) |
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2.5 Changing the rate of learning - Breakpoints |
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67 | (7) |
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2.5.1 Dealing with a breakpoint in a Unit Learning Curve calculation |
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69 | (4) |
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2.5.2 Dealing with a breakpoint in a Cumulative Average Learning Curve calculation |
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73 | (1) |
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2.6 Learning Curves: Stepping up and stepping down |
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74 | (7) |
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2.6.1 Step-points in a Unit Learning Curve calculation |
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74 | (2) |
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2.6.2 Step-points in a Cumulative Average Learning Curve calculation |
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76 | (5) |
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2.7 Cumulative values of Crawford Unit Learning Curves |
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81 | (15) |
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2.7.1 Conway-Schultz Cumulative approximation |
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81 | (1) |
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2.7.2 Jones Cumulative approximation |
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82 | (3) |
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2.7.3 Cumulative approximation formulae compared |
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85 | (5) |
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2.7.4 Batch or Lot Averages |
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90 | (3) |
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2.7.5 Profiling recurring hours or costs - The quick way |
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93 | (3) |
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96 | (1) |
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97 | (2) |
3 Unit Learning Curve - Cost Driver Segmentation |
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99 | (39) |
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3.1 Learning Curve Cost Driver studies -What others have said |
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100 | (4) |
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100 | (2) |
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102 | (2) |
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3.2 Cost Driver changes and breakpoints |
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104 | (10) |
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3.2.1 Output rate: Driver or consequence of learning? |
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104 | (7) |
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3.2.2 End-of-line effects on learning |
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111 | (3) |
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3.3 Segmentation Approach to Unit learning |
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114 | (21) |
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3.3.1 Stopping and starting from where we left off |
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118 | (3) |
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3.3.2 What if we invest more or less up-front? |
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121 | (5) |
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3.3.3 Rate affected learning revisited |
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126 | (2) |
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3.3.4 Parallel v serial working |
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128 | (2) |
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3.3.5 Calibrating the Cost Driver segment contributions |
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130 | (5) |
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135 | (2) |
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137 | (1) |
4 Unlearning and re-learning techniques |
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138 | (28) |
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139 | (1) |
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4.2 Anderlohr's technique |
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140 | (4) |
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4.3 An alternative Simplified Retrograde Technique (not recommended) |
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144 | (1) |
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4.4 Segmentation Technique |
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145 | (5) |
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4.5 Comparison of re-learning techniques |
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150 | (2) |
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4.6 Calibrating the level of learning lost |
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152 | (12) |
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4.6.1 Calibrating the level of learning lost using the Segmentation Technique |
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152 | (8) |
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4.6.2 Calibrating the level of learning lost using the Anderlohr technique |
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160 | (4) |
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164 | (1) |
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165 | (1) |
5 Equivalent Unit Learning |
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166 | (44) |
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5.1 The problems with traditional Unit Learning Curves |
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166 | (6) |
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5.2 Development of the Equivalent Unit Learning theory |
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172 | (15) |
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5.2.1 EUL confidence and prediction intervals |
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184 | (3) |
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5.3 Equivalent Unit Learning and breakpoints |
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187 | (3) |
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5.4 Double-Bunking data for early debunking of breakpoints |
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190 | (8) |
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5.5 Equivalent Unit Learning and achievement mortgaging (progress optimism bias) |
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198 | (4) |
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5.6 Using Equivalent Unit Learning as a top-down validation |
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202 | (4) |
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5.7 Benefits of using Equivalent Unit Learning |
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206 | (2) |
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208 | (1) |
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208 | (2) |
6 Multi-variant learning |
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210 | (38) |
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6.1 Multi-variant Learning Curves |
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210 | (12) |
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6.1.1 Option 1: Ignore Differences (ID) |
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212 | (4) |
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6.1.2 Option 2: Fixed Factors (FF) |
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216 | (1) |
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6.1.3 Option 3: Total Separation (TS) |
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217 | (2) |
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6.1.4 Option 4: Proportional Representation (PR) |
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219 | (3) |
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6.2 Multi-variant Learning Curve model calibration |
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222 | (22) |
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6.2.1 Calibration with the ID approach |
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225 | (4) |
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6.2.2 Calibration with the FF approach |
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229 | (4) |
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6.2.3 Calibration with the TS approach |
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233 | (3) |
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6.2.4 Calibration with the PR approach |
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236 | (3) |
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6.2.5 Comparison of results |
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239 | (5) |
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6.3 Cross-product organisational Learning Curve models |
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244 | (3) |
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247 | (1) |
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247 | (1) |
7 Time-based Learning Curves |
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248 | (18) |
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7.1 Time-Performance Learning Curve |
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249 | (5) |
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7.2 Bevis-Towill Time-Constant model |
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254 | (8) |
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7.3 Cross-product organisational Learning Curve models revisited |
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262 | (2) |
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264 | (1) |
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265 | (1) |
8 The cost impact of collaborative working |
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266 | (11) |
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8.1 Collaborative development costs with equal workshare partners |
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267 | (4) |
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8.2 The collaborative development with unequal workshare partners |
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271 | (4) |
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8.3 Production cost implications of collaborative working |
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275 | (1) |
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276 | (1) |
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276 | (1) |
Glossary of estimating and forecasting terms |
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277 | (19) |
Legend for Microsoft Excel Worked Example Tables in Greyscale |
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296 | (1) |
Index |
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297 | |