Zero-cost, non-commercial, registration-free resources for learning about forecasting

The search for information about time series forecasting and other predictive methods

By Russell L. Kratowicz, P.E., Executive Editor

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According to the Employee Relocation Council Summary Appraisal Report, the definition of forecasting is "the process of analyzing historical trends and current factors as a basis for anticipating market trends." In its simplest terms, the definition concerns itself with projecting future trends, demand and performance.

There are several ways to forecast such things. On one extreme, someone can make a wild guess, take a stand and defend it using words, arguments, tantrums and other suitable weapons against those who might be so bold as to question the forecast's figures and the implications that flow therefrom. At the other extreme, one can take the longer, more difficult route and do the hard work that allows the forecasting statistics do the heavy lifting involved with defense.

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This month, we're probing the depths of that chaos we call the Web in search of zero-cost, non-commercial, registration-free resources aimed at providing you with practical information about forecasting.

What others have said

Forecasting been around for quite some time. I suppose it started with someone actually believing they could read chicken entrails. During the years, many people have commented on the discipline. Read the examples listed in the Famous Forecasting Quotes, http://www.met.rdg.ac.uk/cag/forecasting/quotes.html.

The basics

As is true with most endeavors worth pursuing, you need at least some basic idea of the specialized terminology that goes with forecasting. To start, I direct your attention to the Forecasting Dictionary brought to you by the good folks at The Wharton School of the University of Pennsylvania. This substantial work is found at http://morris.wharton.upenn.edu/forecast/dictionary/.

Frequently asked questions

Forecasting is a mathematically intense effort that can yield good results for those inclined to tackle the subject. Start with the International Institute of Forecasters, a non-profit organization founded in 1981 to stimulate the generation, distribution and use of knowledge on forecasting. The IIF publishes Frequently Asked Questions About Forecasing at http://www.ms.ic.ac.uk/iif/FAQs/faqs.htm.

Margin of error

You've heard newscasters discuss some survey or another and finish by saying something similar to, "The survey of 275 households gave an expected margin of error of three percent." Did you ever wonder about the connection between the number of responses and the margin of error? It should be intuitively obvious to even the most casual observer that surveying a large sample yields more accurate results. The relationship is nonlinearthat's for sureand you can explore it using a statistical calculator provided by the Grapentine Co., Inc., Ankeny, Iowa. Go to http://www.grapentine.com/calculator.htm for the details. Plug in your own numbers. Assume there are 280 million people in this country. Figure out how many surveys you'd really need to predict something of national scope within one or two percent.

Another site owned by Surveyguy, Hatboro, Pa., offers an explanation of the concept of margin of error. Zip on over to http://www.surveyguy.com/homepage.shtml, click on "White Papers" at the left of the home page, then bounce your mouse on What Is A Margin of Error? to get the explanation.

Time series forecasting

The technical definition of a time series is an ordered sequence of values of a variable at equally spaced time intervals. Examples might include the number of work orders initiated every day, the total number of departmental overtime hours worked each week or the total number of ad pages in each issue of your favorite monthly trade magazine. In any case, the general idea is to start with a tabulation of relevant data going back a sufficient number of time periods and apply various numerical procedures in search of a valid mathematical model that can be manipulated to predict future outcomes.

Dr Tony Robinson at the University of Bath in the UK teaches statistics and forecasting. He's posted a series of detailed class notes at http://www.bath.ac.uk/~masar/math0118/forecasting/forecasting.html. Think of it as a densely packed Powerpoint presentation, but without the distracting special effects, which probably explains why Robinson's slides load a lot faster.

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