Quote from harrytrader:
http://www.econometric-wave.com/faqs/probability/home.html.html
'Normal Law is qualified as "Natural Law" because of the "Central Limit Theorem" which says that the sum of n random variables belonging to any random law as long as it has a mean and a variance, will tend towards the Normal Law as n grows.'
It is the best fit because of Central Limit Theorem but it requires some assumptions ... that are not valid spontaneously in an industrial production or shewart the inventor of Quality Control would have been useless ... as well as myself when I began in that enginiering field 
. BTW I remember a story of that time that is not so far from the case of the guy above: one day there was a big problem in the factory where I was working on packaging chain of bread: the bread didn't want to fit the box as usual. After investigation it was discovered that a "brilliant" engineer had decided to optimise the cost of the boxes by reducing the tolerance his calculation was too short ... because of his invalid assumption about the normal law distribution of the boxes . As I have quoted already many times : "premature optimisation is the root of all evil". It is Donald Knuth who said that although he is in software this just shows that it is an universal problem. In trading system there is the same : people want to optimise right away without checking assumption because it is easy to do so - just mathematics formulas in books - whereas the hard work is not mathematics calculation.
Unfortunately in nearly any undergraduate and even higher level statistical courses teachers seem to make always believe that normal laws are most often good approximations without saying that "good" can be really subjective ... like this one:
http://davidmlane.com/hyperstat/normal_distribution.html
"One reason the normal distribution is important is that many psychological and educational variables are distributed approximately normally. Measures of reading ability, introversion, job satisfaction, and memory are among the many psychological variables approximately normally distributed. Although the distributions are only approximately normal, they are usually quite close. A second reason the normal distribution is so important is that it is easy for mathematical statisticians to work with. This means that many kinds of statistical tests can be derived for normal distributions. "
Whereas when you read statistical books written not by teachers but by professional statisticians who had worked in industries like Shewart or Deming this is different. For example I have already quoted a french statistical book untitled "Statistical techniques : rational tools for making choices and decisions" written by a chief engineer of Military Air Force) you can read contrary opinion to the book-school point of view of the teacher above:
"Contrary to natural phenomenas, economical phenomenas must take into account the intervention of humans who don't always obey to random law"
Later on he says that not only it don't always obey to random law but most frequently it doesn't
.
Walter Shewart in 'Statistical method from the viewpoint of Quality Control'" said :
"When a 'scientist' makes an error by using statistical theory it becomes a 'scientific law', but when an industrial statistician makes such error he will sure be accused and have big problems."
Contrary to common opinions, he insist in a whole chapter that statistical rigor in industry involving series production has to be much more harsh than in science because in such cases statistical errors will have effect on millions of products and immediatly the person responsable of that will be hanged. He says that since conditions on industry is much less controllable than in science laboratories one musn't be loose with hypothesis by conveniency but on the contrary must be even more carefull with the hypothesis.
