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Parametric cost estimating, when properly used, is a powerful and cost effective technique. Unfortunately, it is often misunderstood and rejected by many potential users for whom it could be a beneficial tool. An agreement on how to use it and how to recognise its limitations is a major benefit to the cost estimating community. This book presents ways of parametrically forecasting costs and their advantages and disadvantages with examples from the mechanical, software and building industries; it discusses most of the mathematical procedures useful for parametrically forecasting costs and…mehr
Parametric cost estimating, when properly used, is a powerful and cost effective technique. Unfortunately, it is often misunderstood and rejected by many potential users for whom it could be a beneficial tool. An agreement on how to use it and how to recognise its limitations is a major benefit to the cost estimating community.
This book presents ways of parametrically forecasting costs and their advantages and disadvantages with examples from the mechanical, software and building industries; it discusses most of the mathematical procedures useful for parametrically forecasting costs and introduces the judgement needed to audit the ways these techniques are used, firstly as a process and secondly as a tool to generate estimates.
Volume 2 "Building a Specific Model" focuses on the building of ‘specific’ cost estimating models. Understanding the procedures is key in creating successful specific models; so all these procedures (classical and new) are described in this volume.
Pierre Foussier is manager of 3f, the company he founded in 1992 dedicated to the improvement of cost-estimating tools. In his job he develops parametric cost models and trains users of these models. As well as training project managers in cost-estimating, he often acts as a consultant for many diverse companies, carrying out independent cost estimates.
Foussier is a co-founder of AFITEP – a French non-profit organisation specialising in the progress of cost-estimating, planning and project management. He is also the founder of XPAR, a non-profit organisation aiming to promote the parametric method of cost-estimating. XPAR recently merged with AFITEP and is now the working group of this society in the domain of parametrics.
So far in his career, Foussier has been involved in the development and production of some equipment and systems for use in the military industry. He has also been an engineer at the French space agency (CNES) and has nearly twenty years experience of cost estimating for major space projects.
Inhaltsangabe
Population and Sample.- From the Sample to the Population.- Describing the Population.- Typical Distributions.- Data Analysis Precedes the Search for a Specific Model.- Data Analysis on One Variable Only.- Data Analysis on Two Variables.- Simultaneous Data Analysis on J + 1 Quantitative Variables.- Working with Qualitative Variables.- Finding the Dynamic Center of a Multi-Variables Sample.- Finding the Center of the Cost Distribution for Choosing a Metric.- Looking for the Dynamic Center: The Bilinear Cases.- Using Several Quantitative Parameters: The Linear Cases.- Using Qualitative Variables.- Non-Linear Relationships.- Studying the Residuals Is as Important as Finding the Formula.- Studying the Additive Residuals.- The Other Residuals.- Building a Specific Model.- From Sample to Population.- Building the Model.
Part 1: Overview.- The Characteristics of a Distribution.- Standard Distributions.- Part 2: Dealing with One Variable Only.- Dealing with Two Variables.- Dealing with Several Quantitative Variables.- Working with Qualitative Variables.- Part 3:-Defining the Distance Between Two Values: Choosing a Metric.- Using the Differences.- Using the First Type of Ratio.- Using the Second Type of Ratio.- Using the Log of the Ratio.- Using the Biweight.- Conclusion.- Part 4: Using One Parameter.- Using Several Quantitative Parameters.- A Particular Case: The 'Ridge' Regression.- Part 5: Introduction.- Defining the Variables.- Part 6: Linearisable Relationships.- Non-linearisable Relationships.- Part 7: Introduction.- The Classical Approach: The Additive Residuals.- The Classical Approach: The Multiplicative Residuals.- The Modern Approach.- Part 8: The Principles.- The Case of One Variable.- The Case of Two Variables.- P Quantitative Variables.- Using Qualitative Parameters.- Part 9: Why Should We Build a Specific Model?.- How Many Variables?.- What Kind of Formula?.- Selecting the Metric.- Quantifying the Quality of the Formula
Population and Sample.- From the Sample to the Population.- Describing the Population.- Typical Distributions.- Data Analysis Precedes the Search for a Specific Model.- Data Analysis on One Variable Only.- Data Analysis on Two Variables.- Simultaneous Data Analysis on J + 1 Quantitative Variables.- Working with Qualitative Variables.- Finding the Dynamic Center of a Multi-Variables Sample.- Finding the Center of the Cost Distribution for Choosing a Metric.- Looking for the Dynamic Center: The Bilinear Cases.- Using Several Quantitative Parameters: The Linear Cases.- Using Qualitative Variables.- Non-Linear Relationships.- Studying the Residuals Is as Important as Finding the Formula.- Studying the Additive Residuals.- The Other Residuals.- Building a Specific Model.- From Sample to Population.- Building the Model.
Part 1: Overview.- The Characteristics of a Distribution.- Standard Distributions.- Part 2: Dealing with One Variable Only.- Dealing with Two Variables.- Dealing with Several Quantitative Variables.- Working with Qualitative Variables.- Part 3:-Defining the Distance Between Two Values: Choosing a Metric.- Using the Differences.- Using the First Type of Ratio.- Using the Second Type of Ratio.- Using the Log of the Ratio.- Using the Biweight.- Conclusion.- Part 4: Using One Parameter.- Using Several Quantitative Parameters.- A Particular Case: The 'Ridge' Regression.- Part 5: Introduction.- Defining the Variables.- Part 6: Linearisable Relationships.- Non-linearisable Relationships.- Part 7: Introduction.- The Classical Approach: The Additive Residuals.- The Classical Approach: The Multiplicative Residuals.- The Modern Approach.- Part 8: The Principles.- The Case of One Variable.- The Case of Two Variables.- P Quantitative Variables.- Using Qualitative Parameters.- Part 9: Why Should We Build a Specific Model?.- How Many Variables?.- What Kind of Formula?.- Selecting the Metric.- Quantifying the Quality of the Formula
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