A new definition has been added to the Forecasting Dictionary. The definition is of the index method; a somewhat neglected forecasting method that dates at least from Benjamin Franklin's time and that rivals regression analysis or econometrics in usefulness and accuracy.  In developing the index method definition, we have been reminded of the untapped potential of the Dictionary for describing terms that are important to the forecasting discipline. We therefore invite suggestions of new terms and for improvements in the definitions of terms that are already defined in the Dictionary. Please send your suggestions to This email address is being protected from spambots. You need JavaScript enabled to view it..

On December 6, 2009, the number of visits to ForPrin.com exceeded 2 million. Visits have, as at May 30 2010, now exceeded 3 million. This equates to an average of more than 5,700 visits a day or more than 2 million a year since December 6. The rate of visits has been increasing, and we expect the total visits to exceed 4 million well before the end of 2010. We would like to thank our visitors for their support. Please spread the news by telling your colleagues and by posting a link on your own site. As always, your forecasting principles news and suggestions on the site are most welcome.

 The U.S. Department of Defense has issued a request for information entitled "Retroactive Statistical Evaluation of Science and Technology (S&T) forecast and forecasting methods." For more information, got the Federal Business Opportunities page here.

 After a 16-year effort, Scott Armstrong’s book, Persuasive Advertising, is now available from Palgrave Macmillan, with a U.S. shipping date of July 20. It presents 194 evidence-based principles. These principles enable advertisers to predict the effectiveness of their ads by using the AdPrinAudit. Further information is provided from the ForPrin.com sister site, AdPrin.com.

 Andreas Graefe and Scott Armstrong developed a model for forecasting U.S. Presidential Elections. It provides fast advice on which issues candidates should focus on in their campaign by using information about how voters perceive the candidates’ ability to handle the single most important issue facing the country. It predicted the winner of the past ten elections with an accuracy of 97% (based on an examination of the forecasts on each of the last 100 days prior to each of the last ten U.S. Presidential elections). A working paper version of the paper, which was accepted for publication in the Journal of Behavioral Decision Making, is available here.