Tuesday, November 6, 2012

Fallacious Overspecificity

This is a happy day. I'm writing about a situation where Tableau is the solution to a particularly pernicious problem. The lubricant, if you will allow me, that frees the stuck gears of informed discourse by elimination a particular point of friction.

I attended a session today at the annual Tableau Customer Conference, TCC 2012—Stat Spotting: A Field Guide to Identifying Dubious Data, by Dr. Joel Best, Professor, University of Delaware.

Dr. Best covered a number of ways in which numbers are misused, often to great effect, in support of a wide variety of claims across the culture. Many of them are only too familiar to those of us who were raised numerate, and it was a great comfort that these abuses of numeracy are a formal topic of rigorous study.

I chose to work in my profession because I believe that facts and data are important aids that people can take advantage of and employ to make better informed decisions. With more than 25 years in BI one recurring theme I've seen is one Dr. Best identified, which goes something like this:

New! Improved! 106.7% cleaner in independent blind evaluations!

703% ROI in just 11 months.

16.7 people are injured every month in their slippers.

Raise your child's IQ by 14.8% in only 16 short weeks!

We can implement your Enterprise BI solution in 23.4 weeks, starting when we begin the discovery phase.

All of the above employ the all too common tactic of using precise values as a persuasive tool. All of them are also lying, using values with a degree of precision that's either impossible to exist, impossible to measure within the standard conventions of arithmetic precision, or simply monkeys-out-the-butt fabrication.

They're all examples of fallacious overspecificity—the use of a numerically precise value for a deceptive purpose without regard for whether the value is or could be real or true.

One of the great advantages of using Tableau is that it dramatically reduces the effort to "check the numbers" and see what, if any, data evidence supports claims that smell of fallacious overspecificity.

Tableau's great virtue is that is makes it simple to explore and examine data. This directly challenges fallacious overspecifiers because of the ease with which the facts and number behind the numbers can be examined to validate or refute the truth of the claim. This benefit is cumulative, as data analysis becomes the norm numeracy increases and eventually the penalties for misreporting or misrepresenting numeric values tilt the cost-benefit assessment strongly in favor of truth and accuracy.

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