Compelling evidence for in vacuo light speed anisotrophy
in [Relativity]
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From: wbbrdr on 17 Apr 2008 23:25 On Apr 17, 6:24 pm, Jerry <Cephalobus_alie...(a)comcast.net> wrote: > > You can do almost anything you want with bad data, if you are > willing to ignore proper error analysis. > Error analysis that is based on a false premise can also lead to good data being painted as bad. I have explained how that happened with Tom Robert's analysis of Miller's data. > > The flyby anomalies are indeed interesting, but unlike the Pioneer > anomaly, there is unlikely to be any "new physics" involved. > Correct. There is nothing new about in vacuo light-speed anisotropy. GR predicts it so has theoretically existed ever since the start of GR. What is new is that Cahill has proved that it can be measured. Of course all mainstream physicists agree that it cannot be directly measured--ie direct measurements of in vacuo light speed will always be c. However, Cahill's latest flyby paper shows that it can be INDIRECTLY measured via doppler effects. His earlier papers showed that it can be INDIRECTLY measured with gas mode interferometers. That is, the MEASURED anisotropy of light-speed IN GASES can be used to CALCULATE the in vacuo anisotropy. > > Back to my original question, which you don't want to > answer, for some reason: > I was focussing on other issues. But have answered now below. > Suppose I have a theory that the "true curve" should be a sine > curve half the amplitude of the one suggested by the Miller data, > but 90 degrees out of phase relative to Figure 16 in Cahill's > Aperion paper, i.e. exhibiting a peak where the Miller data > suggests a trough:http://redshift.vif.com/JournalFiles/V11NO1PDF/V11N1CA2.pdf > > There are four rotations from the Joos data that I can average > together to yield a sine curve of the stated characteristics. > See a reproduction of Joos's curves in the following: > http://allais.maurice.free.fr/EtudeFuerxer.pdf > > Am I justified in selecting these four runs as representing > "good data" and rejecting the remaining 18 runs, because the > average of these four match my theory? > I would say it depends if you have a way to distinguish between good data and bad data. If you have no way to tell the difference you had better accept it all. If you can tell the difference, you had better reject the bad data. However, if you reject data, you would have a duty of care to readers to tell them what and why you are doing it. Cahill wrote that: "Out of 22 rotations, only in the one rotation, at 11 23 58 , does the data actually look like the form expected. This is probably not accidental as the maximum fringe shift was expected at that time,based on the Miller direction of absolute motion,and the sensitivity of the device was ±1 thousandth of a fringe shift." I don't have a problem with that.
From: Jerry on 18 Apr 2008 06:11 On Apr 17, 10:25 pm, wbb...(a)gmail.com wrote: > On Apr 17, 6:24 pm, Jerry <Cephalobus_alie...(a)comcast.net> wrote: > > > Suppose I have a theory that the "true curve" should be a sine > > curve half the amplitude of the one suggested by the Miller data, > > but 90 degrees out of phase relative to Figure 16 in Cahill's > > Aperion paper, i.e. exhibiting a peak where the Miller data > > suggests a trough: > > http://redshift.vif.com/JournalFiles/V11NO1PDF/V11N1CA2.pdf > > > There are four rotations from the Joos data that I can average > > together to yield a sine curve of the stated characteristics. > > See a reproduction of Joos's curves in the following: > > http://allais.maurice.free.fr/EtudeFuerxer.pdf > > > Am I justified in selecting these four runs as representing > > "good data" and rejecting the remaining 18 runs, because the > > average of these four match my theory? > > I would say it depends if you have a way to distinguish between good > data and bad data. If you have no way to tell the difference you had > better accept it all. If you can tell the difference, you had better > reject the bad data. > > However, if you reject data, you would have a duty of care to readers > to tell them what and why you are doing it. > Cahill wrote that: > "Out of 22 rotations, only in the one rotation, at 11 23 58 , does > the data actually look like the form expected. This is probably not > accidental as the maximum fringe shift was > expected at that time,based on the Miller direction of absolute > motion,and the sensitivity of the device was ±1 thousandth of a fringe > shift." > > I don't have a problem with that. 1) Joos specifically REJECTED run 11 conducted at 23:58 as a probable instrumental artifact because the amplitude of the fringe shifts during this run was extremely inconsistent with the fringe shifts observed in the twenty-one other runs. 2) Cahill specifically ACCEPTED run 11 conducted at 23:58 and REJECTED all other runs because run 11 agreed with his theory and none of the other runs did. 3) I specifically ACCEPTED four of the runs and REJECTED eighteen runs because the average of these four runs produced a curve that agreed with my theory, and including more runs worsened the fit. Do you notice any difference in the way Joos rejected certain data versus the way Cahill did and the way that I did? Joos's accept/reject criteria were based on considerations of instrumental stability and the internal consistency of the data. Cahill's accept/reject criteria were based on whether the data fit his theory. My accept/reject criteria were based on whether the data fit -my- theory. Joos's rejection of a single outlier used theory-independent criteria, and is considered an acceptable practice. Cahill's selection of the run that Joos specifically rejected was motivated by his belief that this run supported his theory. Theory-dependent data selection is considered an unacceptable practice. My selection of four nondescript runs was motivated by the fact that these runs support my theory. Theory-dependent data selection is considered an unacceptable practice. Jerry
From: Surfer on 18 Apr 2008 08:10 On Apr 17, 1:50 pm, Tom Roberts <tjroberts...(a)sbcglobal.net> wrote: > wbb...(a)gmail.com wrote: > > On Apr 17, 6:01 am,TomRoberts<tjroberts...(a)sbcglobal.net> wrote: > >> You must READ MY PAPER. I derived an errorbar > > > by misinterpreting signal fluctuations as measurement errors. > > So your errorbar is completely invalid. > > Not true. My errorbar is derived directly from the raw data, without any > signal dependence at all. It shows that the DATA THEMSELVES, using > Miller's analysis technique, are not capable of displaying any > orientation dependence (the errorbars from the averaging significantly > exceed the variation in the averages). READ MY PAPER to see this. > > > On Apr 17, 10:03 am,TomRoberts<tjroberts...(a)sbcglobal.net> wrote: > >> > Bottom line: the patterns Miller found are not real, they are > >> > INSIGNIFICANT. > > > Owing to the false premise in your paper you haven't proved that. > > There is no "false premise" -- Here is my explanation of your false premise. ========================== The location of Tom Robert's false premise: The caption under Fig 3. says: "The assumed-linear systematic drift from the data of Fig. 1. The lines are between successive Marker 1 values and the points are Marker 9. These markers are 180 degrees apart, so any real signal has the same value for every corner and every point; the variations are purely an instrumentation effect." This statement is FALSE, because measurements at Marker 1 and Marker 9 were not made simultaneously. So any real FLUCTUATING signal would have different values at the two markers. Light-speed anisotropy caused by motion through a calm and stable medium would give rise to a non-fluctuating signal, but while its reasonable to suppose that light does propagate through a medium, there is NO guarantee that such a medium would be calm and stable. Hence if we wish to discover if a medium exists, the assumption that it is calm and stable is unwarranted. ========================= > > what I did is to apply standard > statistical techniques to the average of a set of data points to derive > an errorbar on the average. > How could you get an valid errorbar doing that, if every data point just happened to be dead accurate? You must have made some assumption as to how to distinguish signal from error. I think the caption under Figure 3 explains what you did. But its a false premise as I explained.
From: Florian on 18 Apr 2008 10:45 Surfer <wbbrdr(a)gmail.com> wrote: > On Apr 17, 1:50 pm, Tom Roberts <tjroberts...(a)sbcglobal.net> wrote: > > what I did is to apply standard > > statistical techniques to the average of a set of data points to derive > > an errorbar on the average. > > > How could you get an valid errorbar doing that, if every data point > just happened to be dead accurate? > You must have made some assumption as to how to distinguish signal > from error. > I think the caption under Figure 3 explains what you did. > But its a false premise as I explained. I think there is a way to discriminate between a noisy regular signal that is accurately measured and pure noise. You have to check the variation of amplitude of the errorbars. If the amplitude remains constant, then there is a good chance that there is a noisy signal. For example, looking at Fig 5 (*), I would say that there is a noisy signal. But you have to calculate the variation of the errorbars to verify it. Still, that would not be a confortable proof of a real signal... (*) <http://arxiv.org/abs/physics/0608238v3> -- Florian "Toute v�rit� passe par trois phases. D'abord, elle est ridiculis�e; ensuite, elle rencontre une vive opposition avant d'�tre accept�e comme une totale �vidence" - Arthur Schopenhauer
From: Dono on 18 Apr 2008 11:41
On Apr 17, 8:25 pm, wbb...(a)gmail.com wrote: > However, Cahill's latest flyby paper shows that it can be > INDIRECTLY measured via doppler effects. You mean by using Cahill's Newtonian explanation for the Doppler effect mixed with a ballistic interpretation of the relativity , Bozo? |