Xref: utzoo comp.theory.dynamic-sys:286 sci.crypt:5218 sci.math.stat:2430 Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!zaphod.mps.ohio-state.edu!sample.eng.ohio-state.edu!purdue!mentor.cc.purdue.edu!pop.stat.purdue.edu!hrubin From: hrubin@pop.stat.purdue.edu (Herman Rubin) Newsgroups: comp.theory.dynamic-sys,sci.crypt,sci.math.stat Subject: Re: Can Chaos Be Predictable? Summary: What do you mean by random? Keywords: chaos, predictability Message-ID: <13867@mentor.cc.purdue.edu> Date: 22 Jun 91 18:29:08 GMT References: <1991Jun20.194552.15875@cunews.carleton.ca> <1991Jun22.140127.3984@elevia.UUCP> Sender: news@mentor.cc.purdue.edu Followup-To: comp.theory.dynamic-sys Lines: 21 In article <1991Jun22.140127.3984@elevia.UUCP>, alain@elevia.UUCP (W.A.Simon) writes: > In <1991Jun22.133638.3258@elevia.UUCP> alain@elevia.UUCP (W.A.Simon) writes: .................... > Before I get skewered on a Hilbert curve, let me rephrase > this. Would the tools of statistical analysis (Chi-Square, > etc...) identify that this sequence is not random ? If you ask whether the marginal distribution approaches the limiting one, Beta(.5,.5) for the particular example, the answer is yes. If you actually tested it using a two-sided test, you would even find the sample distribution converged too fast, but it would take quite a large sample to detect that. But if you looked at pairs, they all lie on a very simple curve, which is very obvious. The chaotic nature is that a slight difference at one point makes a big difference a considerable time in the future. -- Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399 Phone: (317)494-6054 hrubin@l.cc.purdue.edu (Internet, bitnet) {purdue,pur-ee}!l.cc!hrubin(UUCP)