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Principles of Forecasting: A Handbook for Researchers and Practitioners (International Series in Operations Research & Management Science) Paperback – January 31, 2002
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John Aitchison, Director of DataSciencesResearch (www.DataSciencesResearch.com)
`This very readable handbook provides a comprehensive synopsis of the entire field of forecasting. The editor, Scott Armstrong, is highly qualified to pull together such a volume. He has been centrally involved in the development of the subject for more than two decades. Armstrong's publications cover the field, ranging from econometric modeling and the extrapolation of time-series data, to role playing and opinion-based forecasting; he is the author of the equally comprehensive book Long-Range Forecasting, which was published in 1978...In sum, Principles of Forecasting is a very handsome volume. It will be a welcome addition to any applied research library, and it should be kept near at hand by any statistician.'
Journal of the Royal Statistical Society, Series D, The Statistician (forthcoming in 2003)
(For the complete review, please check: forecastingprinciples.com)
`... Armstrong's book goes beyond its stated goal of presenting the state of the art of forecasting research in the form of concrete principles; it sets the tone and direction for all future work in this area. The book has earned its place as the bible for forecasters and is a "must have" in every forecaster's library.'
Journal of Marketing Research, XXXIX (2003)
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Top Customer Reviews
Principles of Forecasting is not a book that you will find in airport bookstores. It is not a popular management title that dishes-up the latest buzzwords. On the contrary, this book will give you knowledge to examine critically the fashions and fads, as well as the received wisdom, of management. And yet, despite being a serious work, the book is a joy to read at length, or to browse. I suspect many decision makers will tend to do the latter.
The Forecasting Dictionary is part of Principles of Forecasting and is a good place to start some directed browsing. For example, experienced decision makers will often rely on their intuition, even for important decisions. Is that a good idea? The Forecasting Dictionary has an entry for "intuition" that tells us, "... it is difficult to find published studies in which intuition is superior to structured judgment". Highlighted terms, such as "structured judgment" in the preceding passage, indicate that there is a separate Dictionary entry for the term.Read more ›
Risk analysis has dealt more with subjects like natural and technological disasters. Business forecasting resembled risk analysis in several ways, but over the years, enterprise and capital markets accumulated much more extensive data. Social scientists studied the process of (and procedures for) forecasting with financial data intensively. Small wonder, as poor forecasting often led to costly disasters.
The authors wrote the Handbook in clear, coherent prose. It assembled 29 articles by 40 leading experts into an excellent book with 18 chapters. Armstrong, the editor (and clearly the instigator) created a hierarchical framework that described the relationships between different kinds of forecasting information, beginning with either judgmental or statistical sources. "Principles of Forecasting" illustrated this framework in an often repeated diagram.
The framework contributed to a coherent structure. Each chapter described one compartment within the framework. Each had an introduction that described the limitations and uses of a source of data used by forecasters. Each article also started with an abstract. Thus, a reader could quickly survey all of forecasting by skimming through the Handbook and reading either the article abstracts or the chapter introductions.Read more ›
The final chapter of this book contains 139 forecasting principles...
An example of a forecasting principle is: “13.25 Use multiple measures of accuracy”. A primary use for such principles would be as checklists for software developers, researchers, and practitioners to be sure that their work is complete to this level of detail. These are important general principles. Forecasters will need to use other references for the details of forecasting methods.
The Web site for this book is a very valuable resource for forecasters. Some of the resources are: (1) forecasting dictionary [Enter a forecasting term and the Web site returns a definition.] (2) links to forecasting software sites (3) links to forecasting books and reviews (3) links to bibliographies, abstracts, and (for subscribers) full text papers (4) links to conferences on forecasting (5) links to Web sites related to forecasting.
Clear and logical structure, synthetic approach to the subject and the practical knowledge make manual powininen be compulsory volume in the library of every self-respecting forecaster. And not just those who deal with short-term forecasting.
This textbook is a mine of practical knowledge for studetnów, practitioners and theoreticians forecasting. Special words of appreciation to the editor Professor J. Scott Armstrong of the Wharton School, University of Pennsylvania, a man with a real passion of forecasting.