I left this as a 'comment' on another (economics) blog the other day whose readers I have high regard for, and was shocked at the degree of misunderstanding/animostiy it generated. Yet as one who never seems to shirk from controversy from what I see as injustice, I thought I would add it to my own blog (please trust I am not schizophrenic) as I see the issues/controversies/misunderstandings it generated with other readers as being in fact the very same issues causing escalating health care costs in this country (a subject dear to my own heart). The issue is and always has been about trust...
As another addendum, I pretend to be nothing more than an 'amature' in the philosophy of science. Yet I see that philosophy as having very 'practical' implications to my own interests, so I thought I would add this here...
Are you familiar with Benoit Mandelbrot? He is a mathematician at Yale who wrote a non math book for us 'lay readers' called The Misbehavior of Markets.
As a way of legitimizing the book/author, another author you may have heard of-- Nassim Nicholas Taleb-- famous for Fooled by Randomness and The Black Swan, dedicated The Black Swan to Mandelbrot-- "A Greek among Romans".
Anyway, The Misbehavior of Markets tries to explain to us 'lay' (i.e. non-math) readers the difference between the two major types of risk/statistics that mathematicians use to describe the world:
1. Gaussian risk/statistics (which give 'The Bell Shaped Curve')
2. Cauchy or Lorentz risk/statistics (which give Fractals, Chaos Theory and Power Laws
Most people understand Gaussian statistics intutively-- we use them everyday to analyze things like casino gambling, coin tossing, etc...
Most people DO NOT understand Cauchy statistics intuitively at all. Most people therefore incorrectly misapply Gaussian statistics to problems that are fundamentally Cauchy and they end up with incorrect results (Daniel Kahneman, a psychologist, who won the 2002 Nobel Prize in economics, for his work on heuristics, would call this an example of a flawed heuristic for those who understand me)
Gaussian analysis/statistics work fine for things of 'small variation'-- height, IQ, weight, 'Six Sigma' manufacaturing quality control programs, etc...(just like Newtonian physics 'works fine' when applied at 'slow speeds').
However Gaussian analysis is fundamentally incorrectly applied to things of 'tremendous variation'-- things like wealth, knowledge, names, language, the internet, the stock market, etc...
... and interestingly enough, things of tremendous variation just happen to be most of the things people find meaningful/willing to go to war over-- wealth, love, hapiness, social justice, fairness and income distributions, etc...
When you get into talking about economic issues like 'fairness' and 'social cooperation' AND you apply Gaussian analysis, you will come up with inaccurate results. You are using the wrong statistical tool. If you built a home with simmilarly incorrect math, the home would fall apart.
It was just these issues that Joshua Epstein and Robert Axtell of The Brookings Institution accidentally stumbled upon when they started working on a project called SugarScape.
Sugarscape has profound implications to almost every single article you have written. Sugarscape clearly proves how most economists try to 'solve' issues using the wrong (i.e. Gaussian) mathematics.
In particular, Sugarscape shows how most economists beliefs on 'what is fair' and what is 'socially just' (which by the way have been my own until I learned this) are based on Gaussian logic and reasoning (since most of our minds work this way). Yet these problems are not Gaussian probabilities.
Re-ask every one of the question you have asked your readers but next time use Cauchy/Lorentz logic... you have been trying to 'solve' problems with the wrong tool.
You are using an evolutionary relic of how your own mind developed (no foul, we all do this).
The basic point I am trying to make here is that the entire logic of this very discussion is based ON FAULTY ASSUMPTIONS.
The following is a wonderful website to review some of the basic computer simulations researchers in the field of complex adaptive systems have developed. The site was created by by Ankur Teredesai , assistant professor in the department of computer science at the Rochester Institute of Technology