Global Consciousness Project

[T'ai Chi]

You did not point out the error. You just said that I was wrong.

Fibber.

TheEternalVortex, pointed out that you goofed. I echoed it. You then said that you

"forgot to subtract off the mean"

which I pointed out was still(!) wrong, because if you subtract off the mean, you still don't get the correct variance. To which you replied

"Yes, it does. But why you would care is completely beyond me."

and

"Work it out yourself. I'm sure even you can figure out how to sum the squares of the numbers from 0 to 10, and then divide by 11."

So you see, you really are a cynic in skeptics clothing. A true skeptic would have re-worked it then and there without any glib comment. You? Nope.

My argument is that unless they demonstrate that such biases are not present (which they have not done),

What don't you understand about normalizing?

This is really basic stuff, which anybody who has ever done any kind of data analysis should be familiar with.

And they should know how to calculate the variance of 10 numbers.

Why should we just accept on faith that such biases are not present?

Why should we accept your argument on faith that bias (which you haven't shown to be an issue) is an issue even after normalizing?

For example, the bias that you are ranting about.. is it in the positive direction, negative, what? How big is it? I know, I know, you just throw out possibilities...it is not your job to provide any actual numbers.

You really have no idea who you are talking to, do you?

Here it comes..

I am a physicist.

So are Russel and Targ.

A few of the GCP and PEAR people are engineers.

What your day job is is moot, and a pathetic, desperate argument of pseudo-authority. Unless, of course, you work directly with the inner workings of RNGs, which you don't. My job is much closer to the topic than yours is, but you don't see me pulling that card. You must be desperate to think that passes in a debate on a skeptics board.

As BillyHoyt says, 'I am just a strip club bouncer' (even though he works with computers and is not a strip club bouncer). His point is that such arguments by authority don't hold up. Take notes.

I have several papers published in pear reviewed physics journals on the subject, and have given invited lectures on the subject at major physics conferences.

Any on RNGs? No?

I "understand about the variance" quite well, thank you very much.

Then you'll understand that subtracting out the mean still doesn't give you the correct variance as you claimed. I'm sure you understand.... now.

Oops, I didn't ignore. Must be failing memory. Oh well, I still remember how to calculate the variance of 10 numbers.

 

[69dodge]

Originally posted by jzs
They pass the DIEHARD tests, hence we can be assured of their randomness quality

We can?

Just above, you asked "Who said guaranteed?".

Is "assured" different from "guaranteed"?

 

[Stimpson J. Cat]

jzs,

I thought you had me on ignore?

You did not point out the error. You just said that I was wrong.

Fibber.

TheEternalVortex, pointed out that you goofed. I echoed it. You then said that you

"forgot to subtract off the mean"

which I pointed out was still(!) wrong, because if you subtract off the mean, you still don't get the correct variance. To which you replied

"Yes, it does. But why you would care is completely beyond me."

and

"Work it out yourself. I'm sure even you can figure out how to sum the squares of the numbers from 0 to 10, and then divide by 11."

Like I said, you did not point out the error. You just said that I was wrong.

So you see, you really are a cynic in skeptics clothing. A true skeptic would have re-worked it then and there without any glib comment. You? Nope.

What on Earth does that have to do with skepticism?

My argument is that unless they demonstrate that such biases are not present (which they have not done),

What don't you understand about normalizing?

Good grief! Is it really possible that after all of this time you still don't understand that my argument was that their normalization procedure is flawed???

Why should we just accept on faith that such biases are not present?

Why should we accept your argument on faith that bias (which you haven't shown to be an issue) is an issue even after normalizing?

You shouldn't. I have explained with cold hard math exactly why it is. I cannot help it if you do not understand my explanation. I would have been happy to clarify any parts which are unclear, but you have not pointed out any.

For example, the bias that you are ranting about.. is it in the positive direction, negative, what? How big is it? I know, I know, you just throw out possibilities...it is not your job to provide any actual numbers.

That's right, it's not. I don't know what the bias is, or what direction it is in.

The point is that neither do the PEAR researchers!!!!

Without that information, the results of their analysis are utterly meaningless.

I am a physicist.

So are Russel and Targ.

A few of the GCP and PEAR people are engineers.

What your day job is is moot, and a pathetic, desperate argument of pseudo-authority. Unless, of course, you work directly with the inner workings of RNGs, which you don't. My job is much closer to the topic than yours is, but you don't see me pulling that card. You must be desperate to think that passes in a debate on a skeptics board.

I have not made any sort of argument from authority. I have never asked, nor expected, anybody to simply accept my arguments because I am a physicist. I pointed this out solely to refute your demonstrably false implication that I do not understand basic statistics. I do, and can easily prove that I do. Your representation of a trivial arithmetic error as evidence that I do not, is nothing more than a blatant attempt to discredit my arguments without actually addressing them. It is a classic example of the ad-hominem fallacy. Rather than actually address my arguments, you simply reject anything I say on the basis that if I can make a simple arithmetic error, my arguments can't possibly be valid.

You must have an incredibly low opinion of the people on this board if you think that such dishonest and underhanded tactics are going to distract them from the fact that you have completely failed to offer any substantial counter to my criticism of the PEAR methodology.


Dr. Stupid

 

[T'ai Chi]

[B
Like I said, you did not point out the error. You just said that I was wrong.

[/b]

I said that if you subtract off the mean, you still don't get the correct variance. That is pointing out an error. And you didn't check it before replying to me, saying I was wrong.

I have explained with cold hard math exactly why it is.

You didn't show the level of bias which is what your argument hinges upon. If it is tiny, as it is typically after normalizing, your poitns are not convincing.

That's right, it's not. I don't know what the bias is, or what direction it is in.

The point is that neither do the PEAR researchers!!!!

Oh I see, so you are justified in saying they don't know, but no one dare say that you don't know? Is that how it works?

I pointed this out solely to refute your demonstrably false implication that I do not understand basic statistics.

Well you telling me that the variance calculation was correct if you subtract the mean out certainly demonstrated something.

I guess you don't have any publications relating to RNGs. Could you be mistaken? No, not possible!!

You must have an incredibly low opinion of the people on this board if you think that such dishonest and underhanded tactics are going to distract them from the fact that you have completely failed to offer any substantial counter to my criticism of the PEAR methodology.

Talk about dishonest. You still haven't really showed anything of substance, despite your belief and rantings.

 

[Robin]

The sum of the squares of n independent standard normal variables has a chi-square distribution with n degrees of freedom.

The problem is that it is not a sum of squares, it is a sum of z^2-1, which is not a measure I have come across before and would be interested to know how they calculated the confidence bands.

But, of course, then you need to assume that their z scores really would be normal and independent in the absence of paranormal influences.

Which is why you would need a measure of expected values.

I'd much prefer a resampling type of analysis that doesn't make those assumptions. The GCP has a list of "global events," and their calculation of a p-value is based on the RNG data gathered during those events. (By definition, p-values less than, say, 0.01 would, if calculated correctly, happen only 1 time out of 100.) To see whether their calculated p-value is actually as rare as it claims to be, they should redo the same calculation repeatedly---but use, on each repetition, the RNG data from randomly chosen time intervals of the same number and lengths as the global events on their list. If, for example, their originally calculated "p-value" is 0.01, but it turns out that in a full tenth of the repetitions, rather than in just a hundredth, the similarly calculated "p-value" is less than 0.01, then the true p-value is 0.1 rather than 0.01.

It sounds like a good idea. First though, I would be interested in the p-values calculated from an equal playing field, rather than the 15-minute,10-minute,1 second etc switch that gets done here. If I have time I may do it.

In any case as I have said previously the values are not outside what you would expect from random data.

 

[jj]

Nope, that's not in other words, that is in your words. Stimpy in fact showed no evidence. Neither have you.

When you claim that we must, you lie. It's that simple. You are the one making tthe assertion. You must address criticisms. We don't have to do anything but point out difficulties. You are making the positive assertion, the burden of proof is entirely and completely yours.

If you make a negative claim, that is a claim, and the burden is on you.

Stuff and nonsense. You have assumed the burden, you stand and deliver.

Just pointing out your confusion. In science, providing evidence is talked about, not proving things, as you often demand. [/B]

A lie. You are dishonestly and maliciously confusing mathematical proof with scientific evidence. Your statement is an unproven, fraudulent misrepresentation.

 

[T'ai Chi]

When you claim that we must, you lie.

When you make a misinformed statement such as that, you lie. If you make a negative claim, that is a claim, and the burden of evidence (not 'proof'; take notes) is also on you.

And don't say "we", jj. You've done less than stimpee here. You may think you are his bulldog, but you come across more like a chihuahua. You don't even speak for most skeptics despite believing you do (ie. "we").

You are the one making tthe assertion. You must address criticisms. We don't have to do anything but point out difficulties.

And that is why you often are mistaken for a deluded cynic. If you make a negative claim, you have some burden. I don't care if you don't like that fact, but that is reality. Truzzi identifies the attitude of your type to a T (source:http://www.anomalist.com/commentaries/pseudo.html).

A lie. You are dishonestly and maliciously confusing mathematical proof with scientific evidence.

If arguments were tv shows, yours would be all laugh track.

Seek the attention you desperately need, elsewhere.

 

[CFLarsen]

I suggest you look up the meaning of 'strawman'. No one is saying "completely random" as you claimed.

OK, so they are not completely random. That's your explanation. Gotcha.

Nothing more to talk about, is there?

Feel free to show me where I claimed that it was not explainable by science.

Isn't that your whole point??

Read it again. I wrote "tends". Do you know what "tends" means?

Yep. But when you don't mention that they are selecting the days, then you are misrepresenting the facts.

What does the analysis say, when they include the whole dataset?

"I'm looking at the actual data, which shows that on days specified in the formal hypothesis registry, the data produced by RNGs that have passed the DIEHARD tests tends to be improbable."

Can you make up your mind here? If the data tends to be improbable, then why are they simultaneously explainable by science?

Feel free to present your analysis. I've asked you before. And you've chickened out before. All the "looking at all the data" we get from your website is your testimony which in terms of evidence, equates to dung, scientifically speaking.

So, don't look at it. Can you do better?

 

[CFLarsen]

So are Russel and Targ.

What the hell are you talking about, you idiot? "Russell" and "Targ" are not two persons. Russell Targ is one person.

A few of the GCP and PEAR people are engineers.

Emphasis on "a few".

Oops, I didn't ignore. Must be failing memory. Oh well, I still remember how to calculate the variance of 10 numbers.

Let it go. Stimpy has admitted his error, and it is nothing but petty of you to keep harping on this forever. You make mistakes too, but you don't see people use that as an excuse to address the points you are making.

Should we refuse to do that, given the fact that you don't even know who the people are you are so fond of referring to?

 

[Stimpson J. Cat]

jzs,

I have explained with cold hard math exactly why it is.

You didn't show the level of bias which is what your argument hinges upon. If it is tiny, as it is typically after normalizing, your poitns are not convincing.

Please either explain why my argument hinges upon the level of bias, or respond to my explanation of why it does not. Simply repeating over and over again that it does, and ignoring my explanations of why it does not, is dishonest.

That's right, it's not. I don't know what the bias is, or what direction it is in.

The point is that neither do the PEAR researchers!!!!

Oh I see, so you are justified in saying they don't know, but no one dare say that you don't know? Is that how it works?

Huh?!!?! I just said that I don't know! Are you even reading what I post?

I pointed this out solely to refute your demonstrably false implication that I do not understand basic statistics.

Well you telling me that the variance calculation was correct if you subtract the mean out certainly demonstrated something.

Yes, it demonstrates that even I can make simple mistakes from time to time. Imagine that.

I guess you don't have any publications relating to RNGs. Could you be mistaken? No, not possible!!

What do my lack of publications regrding RNGs have to do with anything? I am not even making an argument about RNGs, other than that it is known that they are not perfect, which is trivial. My argument is about the analysis methodology. As I have explained before, my arguments would be applicable to any source of data, not just RNGs. Again my point is not that the biases in their data have had a significant effect on their results (thereby invalidating them). My argument is that they they have not shown that the biases in their data do not have a significant effect on their results, and that therefore they have shown that their results are valid.

And of course I could be mistaken. If I am, point out the mistake! Your attempts to paint me as some sort of elitist who demands that everybody have blind faith that everything I say about science is correct, are dishonest and completely out of line.


Dr. Stupid

 

[69dodge]

Originally posted by Robin
The problem is that it is not a sum of squares, it is a sum of z^2-1, which is not a measure I have come across before and would be interested to know how they calculated the confidence bands.

It's not a big problem, because 1 is a constant. If you have a sum of n independent (z² - 1)'s, just add n to the sum, and you'll get a random variable that has a chi-square distribution with n degrees of freedom. I'm pretty sure this is essentially what they do.

 

[T'ai Chi]

What the hell are you talking about, you idiot? "Russell" and "Targ" are not two persons. Russell Targ is one person.

Yes I meant Targ and Puthoff(sp?).

 

[CFLarsen]

Yes I meant Targ and Puthoff(sp?). [/B]

So, you admit to making an error. Should we now refuse to address your points from now on, because you made this error?

 

[T'ai Chi]

Please either explain why my argument hinges upon the level of bias, or respond to my explanation of why it does not.

You've stated it yourself. "Why should we just accept on faith that such biases are not present?" and that you don't know the level of bias or what direction it is in. So you're making a negative claim here. Why don't you analyze the data and answer both of your own questions? You won't, because you believe it is not your job to inquire.

You've said yourself that the frequency of 1's in the stream has probabiltiy .5, no matter what the starting p is. So where does the mean bias come in? What are all these higher level biases you talk about? Do you not know their measure too?

And you still have avoided talking about what happens with the other masks that are used. I wonder why? Oops, not your job to inquire.

You have still not talked about the meaning of a large autocorrelation at lag 1. If you feel this large autocorrelation is an issue, then please, you are invited to predict some time-series. Oops, not your job!

My argument is that they they have not shown that the biases in their data do not have a significant effect on their results, and that therefore they have shown that their results are valid.

You have not shown anything to demonstrate your negative claims.

And of course I could be mistaken. If I am, point out the mistake! Your attempts to paint me as some sort of elitist who demands that everybody have blind faith that everything I say about science is correct, are dishonest and completely out of line.

Yet you're the one who pulled the 'Do you know who you are talking to? I am a physicist.' card. Look, I still do not care if you look at rat neurons or whatever. It is your arguments I am concerned about, and the are simply raising the possibility of something, asserting a negative claim, not inquiring, and believing that is a hard-hitting skeptical analysis.

If you think this line of debate is worthless (and I agree), then you shouldn't have brought it up.

Expect chihuahua shortly.

 

[T'ai Chi]

So, you admit to making an error. Should we now refuse to address your points from now on, because you made this error?

My error didn't have to do with the specific mathematical details we are addressing, which is variance calculations. He goofed, twice, on calculating the variance of 10 numbers, and, more importantly, as I've said and you ignore, when I called him on it, he refused to believe me and ridiculed me.

You, stupidly and predictibly, will keep ignoring that last part.

 

[CFLarsen]

My error didn't have to do with the specific mathematical details we are addressing, which is variance calculations. He goofed, twice, on calculating the variance of 10 numbers, and, more importantly, as I've said and you ignore, when I called him on it, he refused to believe me and ridiculed me.

You, stupidly and predictibly, will keep ignoring that last part.

Awwwwwwww.... Justin got a boo-boo? Justin was not treated right?

Justin stomps his foot and throws a tantrum! Justin runs off and tells!

Why don't you grow up, instead of collecting insults like other people collect stamps?

 

[T'ai Chi]

Awwwwwwww.... Justin got a boo-boo? Justin was not treated right?

Justin stomps his foot and throws a tantrum! Justin runs off and tells!

Why don't you grow up, instead of collecting insults like other people collect stamps?

Like I predicted, you ignored the point.

Thanks for being a bullying cynic. You annihilate your own arguments with such ease.

 

[CFLarsen]

Like I predicted, you ignored the point.

Thanks for being a bullying cynic. You annihilate your own arguments with such ease.

Oh, I think I addressed why you are here. Please prove me wrong:

If the data tends to be improbable, then why are they simultaneously explainable by science?

What does the analysis say, when they include the whole dataset?

 

[T'ai Chi]

Bully, seek the attention you desperately need, elsewhere.

 

[CFLarsen]

Bully, seek the attention you desperately need, elsewhere.

Revealing that you find questions "bullying".