Name: Principles, Process and Practice of Professional Number Juggling (en Inglés)
Price: 268521.00 COP
Availability: InStock
Author: Jones, Alan
ISBN: 9781138063969

portada Principles, Process and Practice of Professional Number Juggling (en Inglés)

Formato

Libro Físico

Autor

Alan Jones

Editorial

Routledge

Año

2018

Idioma

Inglés

N° páginas

242

Encuadernación

Tapa Dura

Dimensiones

23.6 x 16.0 x 2.0 cm

Peso

0.52 kg.

ISBN13

9781138063969

N° edición

Categorías

Prospectiva económica
Gestión de proyectos empresariales
Construcción e industria pesada
Planificación de la edificación

Principles, Process and Practice of Professional Number Juggling (en Inglés)

Alan Jones (Autor) · Routledge · Tapa Dura

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Principles, Process and Practice of Professional Number Juggling (en Inglés)"

Principles, Process and Practice of Professional Number Juggling (Volume 1 of the Working Guides to Estimating & Forecasting series) sets the scene of TRACEability and good estimate practice that is followed in the other volumes in this series of five working guides. It clarifies the difference between an Estimating Process, Procedure, Approach, Method and Technique. It expands on these definitions of Approach (Top-down, Bottom-up and'Ethereal') and Method (Analogy, Parametric and 'Trusted Source') and discusses how these form the basis of all other means of establishing an estimate.This volume also underlines the importance of 'data normalisation' in any estimating procedure, and demonstrates that the Estimating by Analogy Method, in essence, is a simple extension of Data Normalisation. The author looks at simple measures of assessing the maturity or health of an estimate, and offers a means of assessing a spreadsheet for any inherent risks or errors that may be introduced by failing to follow good practice in spreadsheet design and build.This book provides a taster of the more numerical techniques covered in the remainder of the series by considering how an estimator can potentially exploit Benford's Law (traditionally used in Fraud Detection) to identify systematic bias from third party contributors. It will be a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering.