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From: Jan Willem Nienhuys To: All Msg #41, Oct-26-92 08:59AM Subject: Re: "Mars Effect": JWN replies Ertel's 23/10 post (pt 2a) Organization: Eindhoven University of Technology, The Netherlands From: wsadjw@rw7.urc.tue.nl (Jan Willem Nienhuys) Message-ID: 6050@tuegate.tue.nl Reply-To: wsadjw@urc.tue.nl Newsgroups: sci.skeptic In article <6049@tuegate.tue.nl> wsadjw@urc.tue.nl writes: ># ># 2.5 Inferential statistics. ># >#Dr. Nienhuys came up with z = 1.23 as deviation of observed Mars- >#born athletes (N = 271/1,076) from chance expectation which he >#estimated as N = 247/1,076 (G% = 22.93%). "Not impressive", he >#says. Error probability would be p = .11, so his statement could >#be rephrased by "not significant" ,i.e., not reaching >#p = .05, the conventional significance level. I calculated from Gauquelin 1972 (or rather from a table quoted there) on the basis of the mentioned 24,961 "ordinary people" that 22.9% is correct. I interpolated the expected values given for the 12-sector distribution (with sectors 1,2,3 and 10,11,12 making up rising and culminating standard sectors) to values for sectors 36 and 9, and arrived at the 22.9%. Originally I had applied the ratio 17.2/16.67 to 8/36, giving about the same. It doesn't matter whether one does it with the theoretical values or the actual observed values in that table. >As Professor Ertel will recall, I estimated the standard deviation >at about 14 absolute, no matter what the exact value was for G%. > >However, the z = 1.23 was computed not from the 22.93 estimate, >but from another one, namely the middle value 23.6 of Ertel's shift >simulations. (Which I told Ertel, on his request). I clearly stated >(I think) that I don't know the "true" expected value. I guess the middle value (from a uniform distribution coming out of Ertel's method) should be discarded. If we believe 22.9%, then this gives z = 1.78. Interesting, unless you insist on two-sided tests. >#Zelen's expectancy of 21.84%. Now, if we use as control 21.84% >#obtained by unsuspected skeptics and essentially confirmed by my >#"replication", the indicator z for CFEPP's Mars G% with athletes >#(N = 271) goes up: z = 2.658 , p = 0.0039. That is, even if we >#follow Dr. Nienhuys' statistical approach and do it correctly the >#result strongly supports the Gauquelin hypothesis. Observe the interesting discrepancy between 21.8 and 22.9, both coming out of a tabulation of results of about 20,000 people. Statistical theory says that the uncertainty in the percentage should be around 0.3 percent. And now we have a difference of 3 times that. "Hurray, again something significant"? (Two-sided at the 0.05 level! Chi-squared = 4.1, 1 df, roughly) Certainly not. No prior hypothesis. No test to check especially that hypothesis. Just an indication that this type of data *might* have more scatter to it than those nice binomially distributed variables from probability theory. JWN BTW, is anybody really interested in this, except Ertel and me? I hate to think that this is degenerating into some kind of SS (siano-sheaffer) dispute.

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