Newly updated 2nd Edition released January 2006:
This tutorial introduces simple methods of reducing the number of false decisions people make based on good data with bad interpretations. Examples are given of diagnosing medical problems, analyzing crime scene evidence, anti-terrorist activities, and several games–including the infamous Monty Hall paradox. Without presenting any specific ways to incorporate decision theory in computer programming, the tutorial does assume that readers will want to go use this introduction to decision making as a first step toward incorporating these methods into other programs such as gaming or picking stocks. We attempt to provide readers with enough of a background that they can incorporate these thoughts into simple computer programs. The tutorial does not require a background in mathematics or formal decision theory. The ability to understand a few simple equations and graphs are all that is required. To learn more, search on Bayes Decision Theory, and you will be flooded with results.

This new version is over 100 pages long with chapters that alternate between discussion of the theoretical aspects and puzzles just for the fun of it. Puzzle lovers will be glad to know that Sherman has included an answers section that includes discussions as to why the answer is correct and how it was obtained. Most of the discussions are expanded compared to what they were in the original column format in Lockergnome’s IT Professionals channel. [ Available in PDF Format for $7 / Download ]