Thank you Francois, Can statistics be rigorously derived from proability math? I hope so. Both are heavily dependent on what appears to be statistics ("both" refers here to my twin gods). I am a self admitted thermodynamics and information science freak. I'd hate to think that my whole world was anecdotally argued. I do see a strange but familiar symmetry between the finite/infinite distinction that seperates probability theory and practice, and the open/closed system maths that seperates the thermodynamic engineering from pure science.
Randall -----Original Message----- From: "Eric Chatonet" <[EMAIL PROTECTED]> To: "How to use Revolution" <use-revolution@lists.runrev.com> Sent: 11/13/2008 9:51 AM Subject: Re: Random algorithm Bonsoir François, Great post indeed :-) I fully agree. Le 13 nov. 08 à 18:47, François Chaplais a écrit : > > Le 13 nov. 08 à 03:39, Randall Reetz a écrit : > >> And another problem is that a random and unique solution actually >> reduces randomness as it is run. Each time you eliminate a >> number, the set of numbers left is reduced. This is even true of >> an infinate number randomizer. Sometimes i wonder if this >> fascination with random number generation isnt a good diagnosis of >> severe case of the geeks. > > maybe it is just a lack of mathematical background >> >> >> -----Original Message----- >> From: "Randall Reetz" <[EMAIL PROTECTED]> >> To: "How to use Revolution" <use-revolution@lists.runrev.com> >> Sent: 11/12/2008 6:18 PM >> Subject: RE: Random algorithm >> >> There is a huge difference between random and unique. If you are >> after unique then just use the counting numbers. If you need both >> random and unique you will have to check each number generated >> against a saved list of every previous number. There is nothing >> wrong with a random number generator that spits out duplicate >> numbers. Random is blind to history (and future). Random is not >> nostalgic. A coin with two sides is just as good at random as a >> pair of thousand sided dice. >> > > actually, random is so little nostalgic that a random sequence of > zeros and ones (with equal probabilities) can produce ones for a > zillion consecutive ones without invalidating the probabilistic > model. This fact holds (mathematically) as long as the number of > events is finite (which is always the case in practice). The > central limit theorem only holds for an "actual" infinite number of > values. > Of course, some may object that having a zillion consecutive ones > is unprobable; however, this assumption itself can only be verified > by repeating the experience an actual infinity of times, so we're > back to the same modelling problem. > > In practice, people do not refer to probabilities but to > statistics. As far as I know there are two schools of statisticians > (at least when it comes to teaching) > 1) the "clean" statisticians present statistics as an offspring of > probabilities; it is mathematically clean but has the same > weaknesses when to it comes to confronting the model to the > experiment. > 2) the "dirty" statisticians admit that if your random process > produces a zillion ones, then you have to pull the trigger on the > model, arguing that modelling the sequence by a constant is closer > to what happens and as economical as the flawed statistical model. > A zillion or two zillion limit: you chose. [truncated by sender] _______________________________________________ use-revolution mailing list use-revolution@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-revolution