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Zusatztext 82961240 Informationen zum Autor Alan R. Jones is Principal Consultant at Estimata Limited, aconsultancy service specialising in Estimating Skills Training. He is a Certified Cost Estimator/Analyst (US) and Certified Cost Engineer (CCE) (UK). Prior to setting up his own business, he enjoyed a 40-year career in the UK aerospace and defence industry as an estimatorAlan is a Fellow of the Association of Cost Engineers and a member of the International Cost Estimating and Analysis Association. Historically (some four decades ago), Alan was a graduate in Mathematics from Imperial College of Science and Technology in London, and was an MBA Prize-winner at the Henley Management College. Zusammenfassung Learning is an empirical phenomenon whereby people or organisations undergo a level of efficiency improvement with recurring tasks. Alan Jones pragmatic guide to this important element within estimating introduces two key learning curve models: Wright and Crawford and explains where, how and when to apply them. Inhaltsverzeichnis Volume IV Table of Contents, 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 Quantity-based Learning Curves, 2.1 A Brief History of the Learning Curve as a Formal Relationship, 2.2 Two Basic Learning Curve Models (Wright and Crawford), 2.2.1 Wright Cumulative Average Learning Curve, 2.2.2 Crawford Unit Learning Curve, 2.2.3 Wright and Crawford Learning Curves Compared, 2.2.4 What's So Special about the Doubling Rule?, 2.2.5 Learning Curve Regression - What appears to be Wright, may in fact be Wrong!, 2.3 Variations on the Basic Learning Curve Models, 2.3.1 DeJong Unit Learning Curve, 2.3.2 DeJong-Wright Cumulative Average Hybrid Learning Curve, 2.3.3 Stanford-B Unit Learning Curve, 2.3.4 Stanford-Wright Cumulative Average Hybrid Learning Curve, 2.3.5 S-Curve Unit Learning Curve, 2.3.6 S-Curve-Wright Cumulative Average Hybrid Learning Curve, 2.4 Where and When to Apply Learning and How Much?, 2.4.1 To What Kind of Task can a Learning Curve be applied?, 2.4.2 Additive and Non-Additive Properties of Learning Curves, 2.4.3 Calibrating or Measuring Observed Learning, 2.4.4 What if we don't have any actuals? Rules of Thumb Rates of Learning, 2.5 Changing the Rate of Learning - Breakpoints, 2.5.1 Dealing with a Breakpoint in a Unit Learning Curve Calculation, 2.5.2 Dealing with a Breakpoint in a Cumulative Average Learning Curve Calculation, 2.6 Learning Curves: Stepping Up and Stepping Down, 2.6.1 Step-points in a Unit Learning Curve Calculation, 2.6.2 Step-points in a Cumulative Average Learning Curve Calculation, 2.7 Cumulative Values of Crawford Unit Learning Curves, 2.7.1 Conway-Schultz Cumulative Approximation, 2.7.2 Jones Cumulative Approximation, 2.7.3 Cumulative Appr...
