Business Forecasting
McGraw Hill Higher Education (Publisher)
5th Edition
Published on 20. December 2005
Book
Mixed media product
978-0-07-320398-0 (ISBN)
Description
The fifth edition of "Business Forecasting" is the most practical forecasting book on the market with the most powerful software - Forecast X. This new edition presents a broad-based survey of business forecasting methods including subjective and objective approaches. As always, the author team of Wilson and Keating deliver practical how-to forecasting techniques, while theory and math are held to a minimum. This edition focuses on the most proven, acceptable methods used commonly in business and government such as regression, smoothing, decomposition, and Box-Jenkins. This new edition continues to integrate the most comprehensive software tool available in this market, Forecast X. With the addition of ForeCastX, this text provides the most complete and up-to-date coverage of forecasting concepts with the most technologically sophisticated software package on the market. This Excel-based tool (which received a 4 point out 5 rating from "PC Magazine", Oct. 2, 2000 issue) effectively uses wizards and many tools to make forecasting easy and understandable.
More details
Edition
5th Revised edition
Language
English
Place of publication
London
United States
Publishing group
McGraw-Hill Education - Europe
Edition type
Revised edition
Illustrations
Illustrations
Dimensions
Height: 228 mm
Width: 177 mm
Thickness: 24 mm
Weight
931 gr
ISBN-13
978-0-07-320398-0 (9780073203980)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Software company producing Forecast X, which will accompany this edition of BUSINESS FORECASTING.
Content
Wilson/Keating, 5/e Brief TOC Chapter 1 Introduction to Business Forecasting Chapter 2 The Forecast Process, Data Considerations, and Model Selection Chapter 3 Moving Averages and Exponential Smoothing Chapter 4 Introduction to Forecasting with Regression Methods Chapter 5 Forecasting with Multiple Regressions Chapter 6 Times-Series Decomposition Chapter 7 ARIMA (Box-Jenkins) -- Type Forecasting Models Chapter 8 Combining Forecast Results Chapter 9 Forecast Implications