The "Process" of John Edward

[Thanz]

Originally posted by BillHoyt

Thanz,

Perhaps you've forgotten that Kerberos' analysis rejected his null hypothesis? My analysis excludes data his included, and my altered analysis rejected my null hypothesis.
I have not forgotton that at all. Kerberos was focussed at the other end of the spectrum - less common initials.

What I did was take his raw counting data, and applied YOUR hypothesis to it. And what I found was that YOUR null hypothesis could not be rejected if we used his counts.

It could also not be rejected if we used my counting methods.

The only analysis which could be used to reject your null hypothesis is the one that you did based on a flawed counting methodology.

I would like to know why you think it is appropriate to count "And they're also talking about somebody who would be known as either Richard or Rich, because a big R-connection that comes up connected to you" as more than one guess. In my count, I counted this as one R guess. From your description, I gather you counted it as 3 R guesses.

[Lurker]

Still exploring the topic of Poisson.

Bill, lets take a step back and try a simple example. Let's say in the census that the letter "J" started in 90% of the population. Now let us say in the LKL transcript JE had a total of 85 guesses of which 80 were "J" guesses.

Apply Poisson just like you did previously arrives at this table, a portion of which I have excerpted:

Count CDF
75 0.461976422
76 0.507613296
77 0.552953827
78 0.597422424
79 0.640483788
80 0.681661216
81 0.72055101
82 0.756832342
83 0.790272365
84 0.820726672
85 0.848135548
86 0.872516699
87 0.893955297
88 0.912592261
89 0.928611673


AM I reading this incorrectly but my interpretation has the Poisson saying there is only a 87% of getting less that 86 "J" guesses in 85 tries. That there is a 13% of getting MORE than 85 "J" guesses in 85 tries.

Is my interpreation correct? IF not, where is it wrong? Thanks for your time.

BTW, results from EXCEL. Try it yourself. It is remarkably easy to set up.

Lurker

[BillHoyt]

Originally posted by Lurker
AM I reading this incorrectly but my interpretation has the Poisson saying there is only a 87% of getting less that 86 "J" guesses in 85 tries. That there is a 13% of getting MORE than 85 "J" guesses in 85 tries.

Your error is in blue. Sadly, I have pointed this out so many times I am now blue in the face.

[BillHoyt]

Let me put you out of your misery, Lurker. There is a 13% chance that you would count 85 "J"s. Period. No qualification on "number of tries". Are you with me yet?

[Walter Wayne]

Lurker with prob of J at 90%, it doesn't make sense, but for N=85 and prob=0.1336 we get the following for binomial and poisson distribution. Note the p=0.05 is at 18 for both.

Walt

[Lurker]

Bill:

Thanks for the response. Recall in our example we took a 85 person sample, just like you did for the "J" analysis. What is the probability according to a Poisson analysis that we would get 85 or less "J"s using p=0.9?

Cheers,

Lurker

[Lurker]

Originally posted by Walter Wayne
Lurker with prob of J at 90%, it doesn't make sense, but for N=85 and prob=0.1336 we get the following for binomial and poisson distribution. Note the p=0.05 is at 18 for both.

Walt

Walt, thanks! This is what I was interested in.

BTW, why doesn't it make sense when p=0.9 in my example provided? Could it be because Poisson is nto a good approximation at that level of p? THAT is what I was trying to get through to Bill which he refused to acknowledge.

Lurker

[Walter Wayne]

Originally posted by BillHoyt
Let me put you out of your misery, Lurker. There is a 13% chance that you would count 85 "J"s. Period. No qualification on "number of tries". Are you with me yet? What?

For poisson distribution, m = pN, and thus the tail moves out as N increases. It would be a horrible tool if it didn't, because if p=0.05 occurs at lets say 18, then one could just count guesses until one gets to 18 and declare success.

Walt

[Lurker]

Originally posted by Walter Wayne
What?

For poisson distribution, m = pN, and thus the tail moves out as N increases. It would be a horrible tool if it didn't, because if p=0.05 occurs at lets say 18, then one could just count guesses until one gets to 18 and declare success.

Walt

Why is it Tai Chi, Lurker, and Wayne all see that N is part of the Poisson distribution yet the self-styled expert, Bill Hoyt, does not?

This seems fairly selfevident.

Lurker

[BillHoyt]

Originally posted by Walter Wayne
What?

For poisson distribution, m = pN, and thus the tail moves out as N increases. It would be a horrible tool if it didn't, because if p=0.05 occurs at lets say 18, then one could just count guesses until one gets to 18 and declare success.

Walt
Walt,

Ask yourself this: what was N for the crows? (See my post to Lurker.)

Cheers,

[BillHoyt]

Originally posted by Walter Wayne
What?

For poisson distribution, m = pN, and thus the tail moves out as N increases. It would be a horrible tool if it didn't, because if p=0.05 occurs at lets say 18, then one could just count guesses until one gets to 18 and declare success.

Walt
Walt,

Ask yourself this: what was N for the crows? (See my post to Lurker.)

Cheers,

[Lurker]

Originally posted by BillHoyt

Walt,

Ask yourself this: what was N for the crows? (See my post to Lurker.)

Cheers,

Ah, here we go with the questions answering question routine...

Good luck Walt, you are going to need it.

Lurker

[BillHoyt]

Originally posted by Lurker


Why is it Tai Chi, Lurker, and Wayne all see that N is part of the Poisson distribution yet the self-styled expert, Bill Hoyt, does not?

This seems fairly selfevident.

Lurker

Argumentum ad populem.

What is N for the crow example?

[BillHoyt]

Originally posted by Lurker


Ah, here we go with the questions answering question routine...

Good luck Walt, you are going to need it.

Lurker

I've already given my answer: you are wrong. I have already given explanations. They are still not getting through. Is my crow example wrong? No. Then ask yourself why it works when we have no N Ask yourself what really moved Walt's tail. (And, no, I'm not getting personal about Walt.:D )

[BillHoyt]

Flash from my Kreskin's Krystal Ball(tm): Walt will get it first.

[Lurker]

Well, if Walt gets it and we are in error I will be the first to apologize.

Lurker

[Lurker]

Originally posted by BillHoyt


I've already given my answer: you are wrong. I have already given explanations. They are still not getting through. Is my crow example wrong? No. Then ask yourself why it works when we have no N Ask yourself what really moved Walt's tail. (And, no, I'm not getting personal about Walt.:D )

Yes, your crow example is wrong. Dreadfully wrong.

Lurker

[BillHoyt]

Originally posted by Lurker


Yes, your crow example is wrong. Dreadfully wrong.

Lurker

Well, then, there you have it! Thanks for contributing to the Tottles.

[T'ai Chi]

Originally posted by Lurker

Why is it Tai Chi, Lurker, and Wayne all see that N is part of the Poisson distribution yet the self-styled expert, Bill Hoyt, does not?

This seems fairly selfevident.

Lurker

Hold on a sec here. :)

The sample size drops out of the probability function. In the Poisson, the sample size, N, is not a parameter.

N is used to estimate lambda, and lambda is used for the Poisson distribution, but this estimation of lambda can be done outside of the Poisson distribution.

So, I guess you can say you can use N in the Poisson as part of calculating lambda, but you can't say that N is a parameter in the Poisson.

But anyway, I doubt the applicability of the Poisson here. If JE just used J's, that would be OK. However, why no one is interested in the other high frequency letters JE uses is beyond me.

[BillHoyt]

Originally posted by T'ai Chi


Hold on a sec here. :)

The sample size drops out of the probability function. In the Poisson, the sample size, N, is not a parameter.

N is used to estimate lambda, and lambda is used for the Poisson distribution, but this estimation of lambda can be done outside of the Poisson distribution.

So, I guess you can say you can use N in the Poisson as part of calculating lambda, but you can't say that N is a parameter in the Poisson.

D*** crystal ball. Another wrong prediction!

Walter, do you see what's really going on with your tail? (No, you don't need a mirror for that. :D )

Cheers,

[Thanz]

Originally posted by T'ai Chi
Hold on a sec here. :)

The sample size drops out of the probability function. In the Poisson, the sample size, N, is not a parameter.

N is used to estimate lambda, and lambda is used for the Poisson distribution, but this estimation of lambda can be done outside of the Poisson distribution.

So, I guess you can say you can use N in the Poisson as part of calculating lambda, but you can't say that N is a parameter in the Poisson.
I had a post that said something like this in the works, but now I can drop it. I think that Lurker is just saying that BillHoyt couldn't calculate the expected number of J guesses without knowing the total number of guesses.

In his crow example, if he knew that the expected number of crows were 5 per acre, and he was shown a field with 9 crows, he would not be able to do his calculations if he also did not know the size of the field with 9 crows.

But anyway, I doubt the applicability of the Poisson here. If JE just used J's, that would be OK. However, why no one is interested in the other high frequency letters JE uses is beyond me.
Hey - I am interested in other letters!

[Walter Wayne]

Originally posted by BillHoyt
Let us say the average number of dead crows per acre is known to be 5. Let us go to Montana and set up 1 acre grids and count in each grid. We see one grid with 9 dead crows and wonder what is the one-tailed probability of that high (or higher) a count. We use a mean of 5, and look at the cdf for >=9. And we get .03.Here you are not doing a binomial approximation (success=1, failure=0), just a count. However, one this is still parameterized by area and acres=1 in this case. If acres=2 then one would use a mean of 10.Now let's go to counting initials. We pick an initial that has a frequency of .5. We count 9 such initials in a field of 10. We use a mean of 5 and look at the cdf for >= 9. And we get .03.

Now let's pick an initial that has a frequency of .05. We count 9 such initials in a field of 100. We use a mean of 5 and look at the cdf for >= 9. We get .03.The mean contains information on poth p and N. N may affect mean, but the mean is not enough to determine N.N, sir, was incidental. Poisson is not affected by it one iota.Would you argue that if y=f(ab), that a is "incidental" to y and that y is not affected one iota. If y=f(ab) then it is sufficient to now ab, but neither a nor b or incidental.

In our case p(x)=f(pN), knowing pN is sufficient, but neither p nor N are incidental.

Walt

Edit: Looks like T'ai Chi answered this before me. However, I disagree with the wording that N "drops out" of the relationship. In our particular case we have set p=0.1336. N is still in the equation. If p = 5/N then N would indeed drop out.

[BillHoyt]

Originally posted by Thanz

I had a post that said something like this in the works, but now I can drop it. I think that Lurker is just saying that BillHoyt couldn't calculate the expected number of J guesses without knowing the total number of guesses.
No, I think the mistake is deeper than that. Otherwise, he would not be construing the Poisson cdfs as "errors" when erroneously contrasting them with his Ns.

[Lurker]

Yes, that is one of the points I am trying to make. Bill could not calculate the mu without n.

And bill, if calling me a totle makes you happy then go right ahead.

And your crow example is still wrong. I suggest you examine it more closely to see your error. With some thought on your part it should become painfully obvious.

Lurker

[BillHoyt]

Originally posted by Walter Wayne
If y=f(ab) then it is sufficient to now ab, but neither a nor b or incidental.

In our case p(x)=f(pN), knowing pN is sufficient, but neither p nor N are incidental.

Walt

If y=f(ab) then y=f(x), and the a and b are incidental. If y=f(a,b), then you have a different story. For Poisson, p(x)=f(mu). Mu is the only thing that is important. Poisson doesn't care how you got the mu.

[Thanz]

Originally posted by BillHoyt

No, I think the mistake is deeper than that. Otherwise, he would not be construing the Poisson cdfs as "errors" when erroneously contrasting them with his Ns.
Regardless, is the rest of my post correct?

You could no more do the analysis of the J guesses without knowing the total number of guesses than you could do the analysis of crows without knowing the size of the field. Correct?

[Lurker]

All right Bill, you keep avoiding this example.

When p=0.9 in the census fo r"J" names. And JE uses 85 initial guesses. What is the probability that in those 85 guesses, that JE will get 85 or less "J" names? 84 or less?

Lurker

[Walter Wayne]

Originally posted by BillHoyt


D*** crystal ball. Another wrong prediction!

Walter, do you see what's really going on with your tail? (No, you don't need a mirror for that. :D )

Cheers, My tail? Are you refering to the fact that the poisson approximation does not yield a 0 pdf for values of x>N. That is why approximations are so fun :)

[Lurker]

Originally posted by Walter Wayne
My tail? Are you refering to the fact that the poisson approximation does not yield a 0 pdf for values of x>N. That is why approximations are so fun :)

And we run full circle to why I wondered about the accuracy of the Poisson Distribution model being valid. I really just questioned it by attempting to show its limitations which Bill refused to acknowledge. Bill seems to defend it with a religious fervor I see only at a Benny Hinn revival.

Since then, others have shown that for the original problem it was fairly accurate which I agreed to. What I find humorous is Bill still insists my questions and demonstrations of the limitations of Poisson are somehow invalid.

Interesting the mind of Bill the Believer.

Lurker

:D :D :D :roll: :roll: :)

[BillHoyt]

Originally posted by Lurker


And we run full circle to why I wondered about the accuracy of the Poisson Distribution model being valid. I really just questioned it by attempting to show its limitations which Bill refused to acknowledge. Bill seems to defend it with a religious fervor I see only at a Benny Hinn revival.

Since then, others have shown that for the original problem it was fairly accurate which I agreed to. What I find humorous is Bill still insists my questions and demonstrations of the limitations of Poisson are somehow invalid.

Interesting the mind of Bill the Believer.

Lurker

:D :D :D :roll: :roll: :)

You and Walt are running in circles. I still hold out hope Walt will get it.

[Lurker]

From http://www.math.uiuc.edu/~hildebr/361/feb14.html

Math 361 at Univ Illinois

"I introduced two important approximations to the binomial distribution, the Poisson approximation and the normal approximation. The Poisson approximation is best suited in the case of rare events and a large number of trials. while the normal approximation works well when the number of trials is More precisely, in order for the Poisson approximation to be accurate, p should be very small, n should be large (ideally of order 1/n), and k should be small (which it almost always is, since the cases of interest are those when k is 0, 1, 2, or some other very small number). If these conditions are not satisfied, the Poisson approximation should not be applied, and it may be completely off."


Bill, what was I questioning about number of trials, probability all effecting the accuracy of Poisson?

Lurker

[Thanz]

Mr. Hoyt -

You have done a whole lot of crowing in this thread, but you have still neglected to answer my question which I believe goes to the heart of the validity of your analysis. Here it is again, in case you missed it:I would like to know why you think it is appropriate to count "And they're also talking about somebody who would be known as either Richard or Rich, because a big R-connection that comes up connected to you" as more than one guess. In my count, I counted this as one R guess. From your description, I gather you counted it as 3 R guesses.

[Lurker]

Thanz:

Bill sure is a good dancer. It is hard to keep hopping about refusing to answer reasonable questions but he seems to have mastered it.

Lurker

[BillHoyt]

Originally posted by Lurker
From http://www.math.uiuc.edu/~hildebr/361/feb14.html

Math 361 at Univ Illinois

"I introduced two important approximations to the binomial distribution, the Poisson approximation and the normal approximation. The Poisson approximation is best suited in the case of rare events and a large number of trials. while the normal approximation works well when the number of trials is More precisely, in order for the Poisson approximation to be accurate, p should be very small, n should be large (ideally of order 1/n), and k should be small (which it almost always is, since the cases of interest are those when k is 0, 1, 2, or some other very small number). If these conditions are not satisfied, the Poisson approximation should not be applied, and it may be completely off."


Bill, what was I questioning about number of trials, probability all effecting the accuracy of Poisson?

Lurker

You really don't understand that paragraph, do you? Go back over it. The Normal distribution is also inaccurate? Huh?

The discussion there, sir, is about using Poisson to approximate binomial. It does not say Poisson is a lesser distribution any more than it says the Normal is a lesser distribution because of the inaccuracies when the normal is used to approximate binomial!

Wow! We have been through this before. Poisson is not "binomial lite". Normal is not "binomial lite". These sources discuss how accurately Poisson and Normal model Binomial.

Now you get my monkey...
http://www.baltobluegrass.com/bbggraph/monkey.gif

Please stop. You are merely demonstrating how militant you can be in your ignorance. Even the monkey is shaking his head.

[Instig8R]

Originally posted by neofight


Concerning anything substantive? No. The only thing that I conceded was that it appeared JE might have been wrong in a part of his interpretation about why the "Malibu Shrimp" recipe was kept "secret".

He interpreted it as meaning that it was secretly based upon one of Deborah's mother's recipes, which he believed was what he was being shown him by her mom, and Deborah said the real reason it was kept secret was because of the questionable clams that she and her friend used when making it, although she did admit that the recipe was based, at least loosely, upon her mom's recipe.

Instig8R feels JE pressured Deborah into admitting that fact, and considers this is a monumental matter. I feel that it could indeed be true, that the recipe was loosely based on one of Deborah's mother's recipes, since most daughters do tend to learn some cooking from their moms.

In any case, I also feel that this whole matter was blown way out of proportion by Instig8R, since the balance of that reading stands, and it was a good reading, with a lot of excellent, accurate hits, and in no way does any of that hinge upon this one, rather irrelevant point.......neo

Hey, neo-- Perhaps the following will help jog your memory... It is our dialogue on 6/25/02 (before you saw the edited reading on television):

(Instig8R)
"Now, I wonder why he didn't ask in what way the sitter's mom contributed to that recipe..."

(neofight):
"Why is that even important? Basically it's been said already. I think it's clear from the context that the woman and her friend simply took one of her mother's recipes that she probably really liked, and improved upon it, adding various ingredients and truly making it a culinary delight. They were probably very proud of the results, and were loath to admit it was not entirely theirs. I would be surprised if there was anything more to the story than that, but it would be nice to find that out for sure....neo"

You seem to have changed your opinion since then. You argued quite vigorously as to the meaning of that hit in June 2002. The "hit" sure seemed relevant in June, 2002. Funny how viewing the edited reading affected your memory and your interpretation of the live reading, isn't it? Memory is a funny thing, isn't it? :)

The point is that JE said that he had Deborah's friend (Helen) and Deborah's mother, together. Mom showed up, specifically to call attention to that stolen recipe. Remember? The recipe was based on something that Mom made, and she never got the credit that she deserved. The point is that JE pressured Deborah into a false validation. She never stole a recipe from her mother, and all those false accusations were edited out of the final reading.

You were so sure, in June 2002, that Deborah would NOT have acknowledged a lie, and you seemed very impressed that JE was let in on that little secret. Yeah, Deborah was busted by the spirits of her mom and her friend. If not for editing, this reading would not have been fit for broadcast.

[Lurker]

Originally posted by BillHoyt


Wow! We have been through this before. Poisson is not "binomial lite". Normal is not "binomial lite". These sources discuss how accurately Poisson and Normal model Binomial.

Now you get my monkey...
http://www.baltobluegrass.com/bbggraph/monkey.gif[/url]

Please stop. You are merely demonstrating how militant you can be in your ignorance. Even the monkey is shaking his head.

Have you derived the Poisson Distribution, Bill? I could be wrong but isn't it derived by taking the limit of the Binomial Distribution as n=>infinity? What implication does this have?

Lurker

[CFLarsen]

Originally posted by Instig8R
The point is that JE pressured Deborah into a false validation.
...
If not for editing, this reading would not have been fit for broadcast.
Two points, impossible to argue against.

[TLN]

Originally posted by CFLarsen
Two points, impossible to argue against.

We'll see... ;)

[Walter Wayne]

Bill,

I think I see what you are getting at. Based on 1 trial, we expect JE to guess J 0.1336 times. If on average over our tests JE guesses J 0.25 times/trial then the p value will be identical.

You are normalizing the units of the average and sample. Instead of comparing the expected 0.1336 J's/trial compared to found 25 J's in 100 trials, you are comparing expected 0.1336 J's/trial to 0.25 J's/trial.

Walt

Edit: My post has some redunancies and repeats itself.

[T'ai Chi]

Originally posted by Thanz

Hey - I am interested in other letters!

Sorry Thanz!!

I should have specified that only Bill is not interested in analyzing the other high frequency letters (at least according to his analysis that only focuses on the high frequency letter J).

[Walter Wayne]

Originally posted by T'ai Chi


Sorry Thanz!!

I should have specified that only Bill is not interested in analyzing the other high frequency letters (at least according to his analysis that only focuses on the high frequency letter J). Actually, somewhere in this thread he mentions that one could also check the theory by seeing if low frequency letters were under represented. I'd quote it, but it is a long thread.

Walt

[T'ai Chi]

I agree with that WW.

My point is that Bill's analyses only consider one letter at a time. He knows that doing the same test multiple times for the letters of interest introduces more error than doing one test that tests several letters at once. If he was interested in testing multiple letters, I'd think he'd find a more appropriate analysis.

[69dodge]

Originally posted by BillHoyt
The discussion there, sir, is about using Poisson to approximate binomial.Certainly.

It is my impression that the discussion here is about the same thing.

[69dodge]

Originally posted by Walter Wayne
I think I see what you are getting at. Based on 1 trial, we expect JE to guess J 0.1336 times. If on average over our tests JE guesses J 0.25 times/trial then the p value will be identical.

You are normalizing the units of the average and sample. Instead of comparing the expected 0.1336 J's/trial compared to found 25 J's in 100 trials, you are comparing expected 0.1336 J's/trial to 0.25 J's/trial.Yes.

The sum of a bunch of independent random variables, all of which have Poisson distributions, itself has a Poisson distribution. The mean of the sum is the sum of the means, which don't have to be identical, though here they are.

Edited to add: I'm not sure what I was thinking when I wrote the above. It's correct, but it's got nothing to do with what you wrote.

I guess I don't quite understand what you wrote, actually. Can you elaborate?

[69dodge]

Originally posted by BillHoyt
Poisson doesn't care about n. If we look at an acre of land and find 12 dead crows, what was the N? Who knows, who cares?The n is the number of crows in the world that could possibly have ended up dead on that acre of land. And p is the probability that any given one of them actually would do so.

We don't care about the exact value of n, but only because we do know that it is much larger than 12.Poisson is not parameterized on N.Quite true. However, if we're considering using a Poisson distribution with parameter np to approximate a binomial distribution with parameters n and p, we should ensure that n is sufficiently large and p is sufficiently small. Otherwise, the approximation will be very poor.

In all the cases that I know about where a Poisson distribution is used, the theoretical justification is that it is an approximation of an underlying binomial distribution with large n and small p. Does anyone know of a different reason why we should expect a physical system to have a Poisson distribution?

[69dodge]

Originally posted by BillHoyt
Now let's go to counting initials. We pick an initial that has a frequency of .5. We count 9 such initials in a field of 10. We use a mean of 5 and look at the cdf for >= 9. And we get .03.Based on your figure of 0.03, I believe you meant '>', not '>='. I will use '>' in the rest of my reply.

I'm not sure what you are claiming. You give an answer of 0.03. But what is the question? I see two possibilities. Let X be a random variable with a Poisson distribution whose mean is 5. What is the probability that X > 9 ?

The answer to this question is 0.0318.

I pick ten letters at random. Each has, independently, a probability of 0.5 of being a J. Let Y be the number of J's that I pick. What is the probability that Y > 9 ?

The answer to this question is 0.000977.

That the answers differ can mean only one thing: Y does not have a Poisson distribution with mean 5. In fact, it has a binomial distribution with n = 10, p = 0.5.Now let's pick an initial that has a frequency of .05. We count 9 such initials in a field of 100. We use a mean of 5 and look at the cdf for >= 9. We get .03.Again, I see two possibilities for what you are asking. same question as before.

same answer as before.

I pick 100 letters at random. Each has, independently, a probability of 0.05 of being a J. Let Z be the number of J's that I pick. What is the probability that Z > 9 ?

The answer to this question is 0.0282.

Again, the two answers differ. And again, this is because Z does not have a Poisson distribution with mean 5. It has a binomial distribution with n = 100, p = 0.05.

However, the two answers are closer than they were before. This is an illustration of the fact that, as n increases and p decreases, with np remaining constant, the binomial distribution with parameters n and p approaches the Poisson distribution with mean np.

[Lurker]

Originally posted by 69dodge
The n is the number of crows in the world that could possibly have ended up dead on that acre of land. And p is the probability that any given one of them actually would do so.

We don't care about the exact value of n, but only because we do know that it is much larger than 12.Quite true. However, if we're considering using a Poisson distribution with parameter np to approximate a binomial distribution with parameters n and p, we should ensure that n is sufficiently large and p is sufficiently small. Otherwise, the approximation will be very poor.

In all the cases that I know about where a Poisson distribution is used, the theoretical justification is that it is an approximation of an underlying binomial distribution with large n and small p. Does anyone know of a different reason why we should expect a physical system to have a Poisson distribution?

You write much clearer than I did but that is what I was trying to get across in my posts which a certain other poster continually argued around.

Lurker

[Thanz]

Originally posted by T'ai Chi


Sorry Thanz!!

I should have specified that only Bill is not interested in analyzing the other high frequency letters (at least according to his analysis that only focuses on the high frequency letter J).
That could be because we don't have enough data to do a more comprehensive test on multiple letters. Of course, Mr.Hoyt won't admit this, and will stick to his flawed J analysis, as it may mean admitting that I was correct when I said the sample size was too small.

[BillHoyt]

Originally posted by 69dodge
In all the cases that I know about where a Poisson distribution is used, the theoretical justification is that it is an approximation of an underlying binomial distribution with large n and small p. Does anyone know of a different reason why we should expect a physical system to have a Poisson distribution?
We are not trying to approximate binomial with Poisson here. We are simply using Poisson. Period. Yes, radioactive decay is a physical system that has a Poisson distribution.

[Thanz]

Originally posted by BillHoyt

We are not trying to approximate binomial with Poisson here. We are simply using Poisson. Period.
Why? What makes Poisson the appropriate tool here?

[Lurker]

Originally posted by BillHoyt

We are not trying to approximate binomial with Poisson here. We are simply using Poisson. Period. Yes, radioactive decay is a physical system that has a Poisson distribution.

And radioactive decay has a near infinite N (atoms) and a small p. I wonder why Poisson is applicable?

Bill, did you find out how Poisson was derived yet? Have you addressed dodge's binomial comparison yet?

Lurker

[Thanz]

Hey! New page - 21!

Since Mr. Hoyt still hasn't answered my question regarding his counting methods, I'll repost it on the new page so he doesn't have to go looking for it.

I would like to know why you think it is appropriate to count "And they're also talking about somebody who would be known as either Richard or Rich, because a big R-connection that comes up connected to you" as more than one guess. In my count, I counted this as one R guess. From your description, I gather you counted it as 3 R guesses.

[SteveGrenard]

I once saw a list of all the names thrown out by a medium and tabulated by Michael Shermer. There were something like 40 names and he said these all happened during the course of a seminar several hours long. This was a misleading statement since half of them were the same name and about a 1/4 were phonetically alike. This exercise proves nothing in such cases.

Richard = Ricky = Rick = Dick = Dicky = Rich = Ritchie

Isnt it possible someone with the name Richard has been called by different people at different times all of those nicks?

[BillHoyt]

I'll repeat my previous post, and add some clarification:
I re-worked the transcripts and came up with different results and a different method. Here it is, in a nutshell:

1. I used the census data figures orginally presented, although these may need tweaking.
2. I excluded the CO show data, and concentrated solely on the available, unedited transcripts from LKL, etc.
3. I looked at JE's style and adjusted the counting procedure as follows:
o I counted all of his name guesses
o Whether he stated them as names or initials, I counted them
o I excluded impossible-to-deal-with things such as "a B softened by a vowel," and chalked that up to a "B" guess.
o I included even bizarre names such as "pepper", "salt", "brooklyn" and other nickname guesses, except that
o I only counted "Liz", "Elizabeth" type guesses as the full given name, and did not also count an "L". but
o When JE recited a littany of names, I counted each one, whether they had the same initial or differing initials (again excluding the "Liz/Elizabeth, Ronny/Ronald, and Bill/William" type guesses, where I only counted the intial of the full given name.

Sound a bit complicated? You should read the transcripts. I could not see another way to approach things fairly given that sometimes he was all over the board. My hypothesis was, that, if there is a JE mediumship process, i should honor as much of it as I could figure in making the counting rules.
Regarding the multiples, I realize this post didn't full explain my reasoning. Sometimes, JE calls out a name or an initial for a person who passed, sometimes for somebody else still living, sometimes he uses the same initial for possibly two different people. Sometimes the names he tosses out are impossible to categorize. "Helen , Ellen or L-name" is a prime example. What the heck do you do there? The first one was H, the second E, the third goes to L. Does he mean L preceded by something? Or L followed? He does the same thing with the "B softened by a vowel" thing. Sometimes he mentions simply a vowel in front. Other times he precedes that vowel with a consonant.

There are three choices as I see them: drop such guesses entirely and thereby lose most of the data, pick one letter and run with it (but which one?) or make a uniform rule allowing him as much leeway as you can. I said I tried to honor his process as much as possible, and I decided to grant him the leeway. The specific leeway I did not grant was "Rich or Richard", where one is clearly a nickname for the other. In those cases, I counted one guess. If he said "Rich or Richard or R" I counted two guesses.

With 26 available letters, and with a focus on just "J", the major distortion I expected was a blossoming denominator. (Clearly, this did happen.) The overall effect I expected was the "J"s would either barely hold onto their significance or that they would be washed out by all the multiple Ds and Rs and Ms and Bs, etc.

[Lurker]

Bill,

Have you had a chance to look into the derivation of the Poisson yet?

For fun, try calculating the odds for getting a heads by flipping a coin three times. List the odds for each total heads as 0 times, 1 time, 2 times and 3 times.

Here is what I got via a probability tree which has zero error:

0 0.125
1 0.375
2 0.375
3 0.125

Making it a cumulative we get

0 0.125
1 0.5
2 0.875
3 1.0

Now I plug this problem into Poisson using mu=np=3*0.5=1.5

0 0.22313016
1 0.5578254
2 0.808846831
3 0.934357546


But wait, Bill, the numbers are different. Why is that? I have provided the EXACT solution and good old Poisson is not very close. Why is that?

Lurker

[BillHoyt]

Originally posted by Lurker
But wait, Bill, the numbers are different. Why is that? I have provided the EXACT solution and good old Poisson is not very close. Why is that?

Lurker

http://www.baltobluegrass.com/bbggraph/monkey.gif
Surprising that you misapply Poisson and see an error?

[Thanz]

Originally posted by BillHoyt
Regarding the multiples, I realize this post didn't full explain my reasoning. Sometimes, JE calls out a name or an initial for a person who passed, sometimes for somebody else still living, sometimes he uses the same initial for possibly two different people. Sometimes the names he tosses out are impossible to categorize. "Helen , Ellen or L-name" is a prime example. What the heck do you do there?
I focussed on how wide a net he was casting. We have already debated whether it is appropriate to consider a guess of simply "John" as equivalent to "J". For the purposes of my count, I considered them equal, although I think a strong argument exists that they are not.

For this specific example, I considered it to be 3 guesses - as he would accept any similar H, E, or L name as a "hit". In this instance, he is using 3 letters to guess one person, so I felt it appropriate to count all three.

The specific leeway I did not grant was "Rich or Richard", where one is clearly a nickname for the other. In those cases, I counted one guess. If he said "Rich or Richard or R" I counted two guesses.
This is where we differ. I consider that to be one guess - as only one intitial letter is involved. He will accept any R name, and he is hoping to be close with Richard. But he is not making two guesses - the net stays only as wide as "R". As we are considering only the letters involved, I considered this to be one guess of the letter R. He is NOT casting 2 R nets here, which is what your count would seem to say.

With 26 available letters, and with a focus on just "J", the major distortion I expected was a blossoming denominator. (Clearly, this did happen.) The overall effect I expected was the "J"s would either barely hold onto their significance or that they would be washed out by all the multiple Ds and Rs and Ms and Bs, etc.
However, that clearly did not happen. Adding in extra "J" guesses has more of an effect than adding in extra letters to the denominator. We have radically different counts. I don't know exactly what transcripts you used, but I used the LKL transcripts posted by Renata and got 9 J guesses out of a total of 43, compared to 18 and 85 for you.

When Kerberos did his count, he counted 78 guesses and 14 Js. The difference between his and yours are 4 Js and 7 total guesses. But the 7 extra total only move the expected by about .6, but the extra 4 Js makes all the difference in whether we can reject the null hypothesis.

[Lurker]

Originally posted by BillHoyt


Surprising that you misapply Poisson and see an error?

Hey, now we are getting somewhere! Finally! Now, how about you tell us when Poisson will be accurate and when it will not.

Thanks!

Lurker

[CFLarsen]

Originally posted by SteveGrenard
I once saw a list of all the names thrown out by a medium and tabulated by Michael Shermer. There were something like 40 names and he said these all happened during the course of a seminar several hours long. This was a misleading statement since half of them were the same name and about a 1/4 were phonetically alike. This exercise proves nothing in such cases.

Richard = Ricky = Rick = Dick = Dicky = Rich = Ritchie

Isnt it possible someone with the name Richard has been called by different people at different times all of those nicks?

Can we see this list, Steve?

[Lurker]

Bill:

I would have thought a math genius like yourself would have been happy as a clam to dive into the derivation of the Poisson Distribution. I wonder why you haven't?:wink:

Could it be because of its relation to the binomial...:D

Lurker

[BillHoyt]

Originally posted by Lurker
Bill:

I would have thought a math genius like yourself would have been happy as a clam to dive into the derivation of the Poisson Distribution. I wonder why you haven't?:wink:

Could it be because of its relation to the binomial...:D

Lurker

Lurker,

You are an absolutely waste of time on this issue. Poisson can be derived from binomial. It can also be derived from geometric. It can also be derived by solving the differential equation:

f(t) = q*(1 - f(t))

The last derivation is from basic radioactive decay.

So what if they can be derived from one another? Don't you understand the Central Limit Theorem?

Now go away.

[T'ai Chi]

I guess we should all use the same readings, and we all should count the J-name occurances, and see what we all get.

Oh, in my opinion Bill probably thinks that JE just does cold readings with the letter J or something.

[Lurker]

Originally posted by BillHoyt


Lurker,

You are an absolutely waste of time on this issue. Poisson can be derived from binomial. It can also be derived from geometric. It can also be derived by solving the differential equation:

f(t) = q*(1 - f(t))

The last derivation is from basic radioactive decay.

So what if they can be derived from one another? Don't you understand the Central Limit Theorem?

Now go away.

My, touchy, aren't you. :) And what does one assume when one derives it from those equations? Hmm? You always seem to avoid that question. Why is that, Bill?

This is getting humorous as Bill frantically tries to avoid giving me credit for any shred of knowledge. It is so much easier for him to debate with ad homs.

Lurker

[Lurker]

Come on, Bill. Enlighten us as to when it is applicable to use Poisson? Others have asked. Seems pretty simple. Why don't you answer?

Is it valid for all values of p?

Is it valid for any population size?

Simple questions for someone as knowledgable as you clearly are. And I do mean that. You clearly understand more about statistics than I do. I fully grant you that. So tell me when Poisson is applicable and when it is not. Two simple questions above.

Lurker

[CFLarsen]

Lurker,

Do you think it would be prudent for people to have a chance to be able to get back to you, before you chastise them for not answering?

Not everyone is on JREF 24/7, you know.

[T'ai Chi]

CF, what do you think of just looking at the J's?

[CFLarsen]

Originally posted by T'ai Chi
CF, what do you think of just looking at the J's?

I'll await the statistical experts.

[TLN]

Originally posted by CFLarsen
I'll await the statistical experts.

See if Girl 6 will help out.

[CFLarsen]

Originally posted by TLN
See if Girl 6 will help out.

I said "statistical", not...oh. OK. :)

[Thanz]

Originally posted by CFLarsen


I'll await the statistical experts.
Why the cop out, Mr. Larsen? You were all over me with stats questions earlier in the thread.

You don't have to be a stats expert to answer some of the basic questions here.

1. Do you think that an analysis of only one letter is meaningful to ascertain whether or not JE is cold reading? If someone were to ask you what you thought was a good test for cold reading comparison, would it be test of one letter or multiple letters?

2. What do you see as the proper counting technique for the following JE (style not a quote) guess: "I am getting a John or Joe or some other J, J-o connection here". How many J guesses would you count out of that?

[TLN]

Originally posted by Thanz
Why the cop out, Mr. Larsen?

Because he's not a statistician and neither are you. Therefore, neither of you are qualified to say what would be statistically significant in this example.

When you've got nothing left but bashing folks based on admissions of ignorance you've got nothing left at all.

[CFLarsen]

Originally posted by Thanz
Why the cop out, Mr. Larsen? You were all over me with stats questions earlier in the thread.

Not a cop out. But I can spot a fake a mile away. I spotted you. And I've watched you, "grilling" BillHoyt on statistcal matters. You're not fooling anyone, you know. You have no idea what you are talking about.

Originally posted by Thanz
You don't have to be a stats expert to answer some of the basic questions here.

I prefer to leave the expert question to the experts. What's wrong with that? You should try it, you know...

[Lurker]

Originally posted by CFLarsen
Lurker,

Do you think it would be prudent for people to have a chance to be able to get back to you, before you chastise them for not answering?

Not everyone is on JREF 24/7, you know.

Claus,

I have been asking the same questions, or variations for over a week now with no answers from Bill. He refuses to answer direct questions. You would know that if you had bothered to read the thread.

Lurker

[Thanz]

Originally posted by TLN
Because he's not a statistician and neither are you. Therefore, neither of you are qualified to say what would be statistically significant in this example.
I am not asking him to give me the derivation of Poisson, or how we should set significance levels, or anything else. I am NOT asking him what is "statistically significant".

I am asking about simple test design. If he doesn't think he is qualified to comment on any of this, why did he attack me earlier? He was asking some very pointed statistically based questions earlier. Much more statistically based than my questions. Shouldn't he have left that to the experts?

Also, since when does someone have to be a statistician to make a comment here? Is Mr. Larsen an expert on fraud? On cold reading? On speaking to the dead? On scientific design? He comments on all of these things.

The questions I have asked are extremely basic, and if Mr. Larsen is as serious as he claims to be about paranormal research he should be able to answer them easily. I chalk his refusal up to simple avoidance. Since when does one need be a statistician to have an opinion on how to count J guesses?

[Thanz]

Originally posted by CFLarsen
Not a cop out. But I can spot a fake a mile away. I spotted you. And I've watched you, "grilling" BillHoyt on statistcal matters. You're not fooling anyone, you know. You have no idea what you are talking about.
How can you know this? You are no "expert" by your own admission..... Oh, I know. Maybe it is because I admitted that I was not an expert. I am not trying to fool anyone, doof.

I prefer to leave the expert question to the experts. What's wrong with that? You should try it, you know...
I am not asking expert questions. I am asking basic test design questions. Is it more meaningful to test all letters or one letter? How should we count a guess of "J"?

You seem to think that you are qualified to comment on the validity of Schwarz's experiments and to design and conduct your own experiments into whether JE is talking to the dead. What expertise allows you to do that, but not answer my simple questions?

[CFLarsen]

Thanz,

Let's see. You are only arguing basic test design questions and not asking expert questions?

Originally posted by Thanz
Needless to say, I get numbers substantially different than BillHoyt's. In the LKL readings posted by Renata, I counted 43 guesses, of which 9 were J. If I plug this into the Poisson calculator, I get a probability of >= 9 of .128, which means that we cannot reject the null hypothesis.
...
One more thing - Kerberos' count of hits was 14 J hits out of 78 guesses. If I pop those numbers into the ol' Poisson calculator, I get a probaility of >= 14 of .168, which also means that we cannot reject the null hypothesis.
...
I am not ignoring the fact that the method was applied equally to all initials. I am saying that the method is incorrect, and leads to incorrect counts for both the J value AND the denominator. Having both numbers wrong leads to a wrong analysis. It just means that ALL of your data is incorrect. I was not accusing you of bias in the data - in that you would count only extra "J" guesses. I am saying that your methodology was flawed from the beginning.
...
That could be because we don't have enough data to do a more comprehensive test on multiple letters. Of course, Mr.Hoyt won't admit this, and will stick to his flawed J analysis, as it may mean admitting that I was correct when I said the sample size was too small.
...
Why? What makes Poisson the appropriate tool here?


These questions are not about test design but definitely expert questions about statistics. And you are definitely a fake, when it comes to statistics. When reading your posts here, it is obvious you take your leads from other posters. Did you know what Poisson was before this thread started?

My "expertise" in commenting on Schwartz' abominations and design my own experiments comes from my studying what has been done, where the flaws are, and how it can be improved.

In other words, I read and learn.

What questions of yours have I not answered?

[T'ai Chi]

Originally posted by CFLarsen

I'll await the statistical experts.

I'll give you an answer: readings are done with more than one letter. Therefore our statistical analysis should reflect that, and we should look at more than one letter. It seems sensible to analyze all the high frequency letters together (there are about 5 or 6 of them).

Bill's counting of the J's and focusing solely on the J, is probably consciously or unconsciously a wish for a rejection of a null hypothesis. I wonder if any statistician would say the analysis is appropriate.

[Thanz]

Originally posted by CFLarsen
Thanz,

Let's see. You are only arguing basic test design questions and not asking expert questions?
Can't you "read and learn" in this thread? Nothing in those posts requires any massive amounts of statistical understanding. The counting method I used to get the counts in the first quote was explained in that post. I thought it was simple and easy to understand. As to the numbers from the Poisson calculation, I used a calculator available on the web and reported the results. Nothing magical here either.

The third quoted portion deals with the counting method, and I am coming to the stunning conclusion that if your counting method is flawed, your data will also be flawed, and you will not get an accurate analysis from flawed data. Is that too hard for your non-expert brain to comprehend?

Finally, asking why he used a certain distribution (Poisson) instead of others is a simple question for someone who understands stats (as BillHoyt claims to) to answer. He picked hte test. I am just asking why.

These questions are not about test design but definitely expert questions about statistics. And you are definitely a fake, when it comes to statistics. When reading your posts here, it is obvious you take your leads from other posters. Did you know what Poisson was before this thread started?
It is called "reading and learning". Of course I take leads from other people in this thread that understand stats better than I do. I'd be an idiot if I didn't. Also, none of those questions were aimed at you. Nice try at diversion. I didn't ask YOU whay Poisson was appropriate, I asked BIllHoyt. I am asking not to trap him, but because I don't know why he chose Poisson. Other people here seem to disagree with him on his chosen test.

As for your specific question, no I did not know what a Poisson distribution was before this thread. I may have heard the term back in my undergrad days, so it was a little familiar, but if pressed I would not be able to explain it. But I ask you, so what? I have learned in this thread how to use the Poisson calculator and apply it to data as presented. I have a limited understanding of what the output of the calculator tells me (I can apply it to the test Mr. Hoyt did here).

My "expertise" in commenting on Schwartz' abominations and design my own experiments comes from my studying what has been done, where the flaws are, and how it can be improved.

In other words, I read and learn.
Just as I have done here.

What questions of yours have I not answered?
Do you really not know? They were specifically directed to you. Here they are again:

1. Do you think that an analysis of only one letter is meaningful to ascertain whether or not JE is cold reading? If someone were to ask you what you thought was a good test for cold reading comparison, would it be a test of one letter or multiple letters?

2. What do you see as the proper counting technique for the following JE (style not a quote) guess: "I am getting a John or Joe or some other J, J-o connection here". How many J guesses would you count out of that?

[BillHoyt]

Originally posted by Lurker
And what does one assume when one derives it from those equations? Hmm? You always seem to avoid that question. Why is that, Bill?


The definition of a Poisson distribution is based on that of a Poisson process. A Poisson process is one that satisfies the following:


1. The changes (or events) that result from the process can be grouped into nonoverlapping intervals.

2. The numbers of changes (or events) in the nonoverlapping intervals are independent from one another.

3. This independence holds for all intervals.

4. The probability of exactly one change (or event) in a sufficiently small interval, h = 1/n equals n*p , where p is the probability of one change (or event) and n is the number of trials.

5. The probability of more than one change (or event) in a sufficiently small interval, h, is essentially 0.

The Poisson distribution results when such a process occurs over n trials.

There are no hard and fast definitions to it, other than the above.

Lurker, you continue to insist that there is a question for me to answer about what one assumes when one derives Poisson from other distributions. This question makes no sense. The assumptions are grounded in the terms of those other distributions to derive Poisson, and are meaningless once you get to Poisson.

Poisson does not make an error when it predicts a p(x) beyond your n. The "n" is not in the Poisson distribution. Look closely at the definition above. "n" comes into play when you design your "bins" (the intervals). It affects your expected mean. Once you decide your expected mean, you have identified everything in Poisson. The "n" is now gone.

[CFLarsen]

Thanz,

There's a difference between learning and parroting. Because you can punch in numbers on a calculator does not mean you understand how the method works.

I have replied to the questions you refer to. I await the experts. Do you have a problem with understanding what people tell you?

[Thanz]

Originally posted by CFLarsen
Thanz,

There's a difference between learning and parroting. Because you can punch in numbers on a calculator does not mean you understand how the method works.
I guess that you are quite familiar with the difference between learning and parroting. In this thread, for instance, the questions that you asked me earlier were clearly "parroting". It is also obvious that you haven't been able to learn anything in this thread.

As for whether I understand how the method works, well, no, I can't derive the Poisson distribution, nor do I know the specific formula. I understand enough, however, to be able to do the various calculations and determine whether we can reject the null hypothesis. Which is apparently more than you have been able to pick up.

You see, at least I am trying to understand. You, however, are simply parroting Mr. Hoyt and avoiding questions that require no expertise in statistics at all. I guess that avoiding questions and giving non-responsive "answers" is your true expertise.

I have replied to the questions you refer to. I await the experts. Do you have a problem with understanding what people tell you?
I have a problem figuring out what part of "What do you see as the proper counting technique for the following JE (style not a quote) guess: "I am getting a John or Joe or some other J, J-o connection here". How many J guesses would you count out of that?" requires any expertise in statistics.

You are familiar with mediums. You are familiar with the guesses they make. Do you not know how to count? Is that it? Do you need a statistician to count for you?

[CFLarsen]

Thanz,

I see you do have a problem with what people tell you. Especially if you don't like it. I notice that you merely dismiss me, while admitting that you have, indeed, no idea what you are talking about. Thanks for proving my point.

You need to understand one thing, though: You do not control the life of other people. You do not have the right to command other people to do what you want them to do. And you have no right to point your finger at them, either.

Do you understand this simple thing, or do we have to go 2589 rounds before you get it?

Have a nice day.

[Thanz]

Originally posted by CFLarsen
I notice that you merely dismiss me, while admitting that you have, indeed, no idea what you are talking about.
I dismiss you as you seem completely unable to come up with any thoughts on the matter on your own. I have by no stretch admitted that I "have no idea what [I am] talking about". You, sir, are a liar. All I have done is admitted the limits of my knowledge, which is more than you have done.

You have simply parroted Mr. Hoyt while asking me questions, giving the impression that you have a clue about what the questions mean. Then, when asked some simple questions that do not require anything close to any expertise in statistics, you say "I'll wait for the experts". Which, in reality, I suspect means "I'll wait and say whatever BillHoyt tells me to say".

You need to understand one thing, though: You do not control the life of other people. You do not have the right to command other people to do what you want them to do. And you have no right to point your finger at them, either.
It will be a long, long time before I get over the irony of being told this by Mr. Larsen, who consistently hounds others and even starts threads with lists of questions that he demands other people answer.

Mr. Larsen, you dish it but you can't take it. You revel in making the lives of "believers" miserable on this forum (and probably other forums). For you to turn around and tell me that I "do not have the right to command other people to do what I want them to do" or "to point the finger at them" is quite simply the pinnacle of hypocrisy.

I trust that this point has been lost on you, however.

I notice, as well, that you can't even explain why you are waiting for the "experts" or what expertise my questions would require.

[CFLarsen]

Thanz,

Have I made claims about my statistical knowledge? Far from it, I believe. Do you understand the difference between making a claim and not making a claim? Here, on this board, claims are questioned. When people don't make claims, they should not be challenged to defend themselves. That's what you are trying to do here.

You do your best to cast doubt about me. You fail miserably, though. Why are you falling back on nasty innuendo about my behavior on other boards? Is that because you have run out of arguments?

You clearly don't like my answers. It is because they don't satisfy you. So, you feel entitled to call me a liar and start imagining my objectives.

Go on, Thanz. Imagine. It's what you do best.

[Lucianarchy]

Originally posted by Thanz

I dismiss you as you seem completely unable to come up with any thoughts on the matter on your own. I have by no stretch admitted that I "have no idea what [I am] talking about". You, sir, are a liar. All I have done is admitted the limits of my knowledge, which is more than you have done.

You have simply parroted Mr. Hoyt while asking me questions, giving the impression that you have a clue about what the questions mean. Then, when asked some simple questions that do not require anything close to any expertise in statistics, you say "I'll wait for the experts". Which, in reality, I suspect means "I'll wait and say whatever BillHoyt tells me to say".

It will be a long, long time before I get over the irony of being told this by Mr. Larsen, who consistently hounds others and even starts threads with lists of questions that he demands other people answer.

Mr. Larsen, you dish it but you can't take it. You revel in making the lives of "believers" miserable on this forum (and probably other forums). For you to turn around and tell me that I "do not have the right to command other people to do what I want them to do" or "to point the finger at them" is quite simply the pinnacle of hypocrisy.



That must be what they call a 'Hot read' then is it?

:roll:

[Thanz]

Originally posted by CFLarsen
Have I made claims about my statistical knowledge? Far from it, I believe.
Some level of statistical knowledge was implied when you were asking me specific statistical questions. Or are you admitting that you had no idea what those questions meant and you were just parroting BillHoyt?

Do you understand the difference between making a claim and not making a claim? Here, on this board, claims are questioned. When people don't make claims, they should not be challenged to defend themselves. That's what you are trying to do here.
Dude, I was just asking for your opinion on a couple of questions. Questions that do not require any expertise in statistics, just some logical and critical thinking skills. Since you can't answer them, I guess you don't have any of those skills.

You clearly don't like my answers. It is because they don't satisfy you.
I don't like your answers because they provide nothing of value to the discussion. Have you provided ANYTHING of value to this entire discussion? Or did you just want to jump in to ask me stats questions that you don't even understand?

Look, if you lack the logical and critical thinking skills to answer my questions, that's fine. Be a dolt. I don't care. Continue on your mission to fight against the "believers" no matter what they actually say.

[T'ai Chi]

Has anyone looked at other letters besides the letter J yet?

[CFLarsen]

Originally posted by Thanz
Some level of statistical knowledge was implied when you were asking me specific statistical questions. Or are you admitting that you had no idea what those questions meant and you were just parroting BillHoyt?

Oh, I had an idea, that's all. That idea was not unfounded. Why do you want to shift the focus from you to me?

Originally posted by Thanz
Dude, I was just asking for your opinion on a couple of questions. Questions that do not require any expertise in statistics, just some logical and critical thinking skills. Since you can't answer them, I guess you don't have any of those skills.

Did I make a claim? If so, what was it? If not, what right have you to demand an answer?

Originally posted by Thanz
I don't like your answers because they provide nothing of value to the discussion. Have you provided ANYTHING of value to this entire discussion? Or did you just want to jump in to ask me stats questions that you don't even understand?

Oh, come off it! You were cornered on statistical issues, and now it's all my fault. Pluhease...!

Originally posted by Thanz
Look, if you lack the logical and critical thinking skills to answer my questions, that's fine. Be a dolt. I don't care. Continue on your mission to fight against the "believers" no matter what they actually say.

Sure, go ahead with the personal attack, in the (vain) hope that your lacking statistical knowledge will not be noticed.

[Walter Wayne]

Originally posted by T'ai Chi
Has anyone looked at other letters besides the letter J yet? Yes. I looked at the three transcripts from Renata's thread. Counting Robbie, Rob or Robert as a single R, I found the following doing very rudimentry stats stuff.

6 J's of 28 is statistically high though not within p=0.05. The next question becomes, what letters where "sacrificed" in order to give more J answers? Were low percentage letters neglected more than the remaining high percentage letters?

Of the remaining 22
2 M's: about right
3 R's : slightly higher than expected
2 from the bottom 14 percentile (P,W,H,N,F,V,I,O,Y,Z,Q,U and X): slightly below expectation

The reason I lumped the bottom ones together is that each of them individual has an expected value less than 1. I chose 14% to lump together because that group of 13 letter the same probability as J alone.

The above are consistant with guessing only high percentage values in order to improve hit rates. J, M and R are guessed often at the expence of the unlikely letters. But nothing came anywhere near a p=0.05.

However, continuing down the high probability letters D, C, A, and S each have 1 guess. Then middling probality letters L and B have 4 and 3 guesses respectively. This appears contradictory to our original conclusion. Why guess L and B so frequently at the expense of some higher probability letters.

So, based on a very small number of readings, JE has affinities for J, M and R as expected and aversion to the low probability letters, also expected. However, he seems to have an "unnatural fetish" for L and B.

Admittedly, I used a less then perfect method for doing analysis on a group of related bins but for my curiousity purposes it was sufficient.

The reason I didn't post this earlier was:
1. I have a probablem with using census statistics. After all he is trying to contact/emulate dead people. So the statistic we should look at are for older people, not the population at large.
2. The number was so small from those three transcript, I didn't think the statistics meant anything anyways.
3. This thread had fallen off the front page, and I had hoped laid to rest. :p

My count from the transcripts, in order from most likely letters to least, was:
28 easily binned guesses
6 J
2 M
3 R
1 D
1 C
1 A
1 S
4 L
3 B
1 E
2 T
1 K
- G
1 P
- W
- H
1 N
- F, V, I, O, Y, Z, Q, U , X

8 guesses in "other"
2 J or G
1 C or K
1 H or E
1 E or L
1 vowel then B
1 vowel then L
1 "spice" name

[neofight]

Originally posted by Thanz
It will be a long, long time before I get over the irony of being told this by Mr. Larsen, who consistently hounds others and even starts threads with lists of questions that he demands other people answer.

Yes, Thanz. The irony is exquisite indeed. And "pinnacle of hypocrisy" does fit Claus quite well. :)

I trust that this point has been lost on you, however.


No doubt.......neo

[neofight]

Originally posted by Walter Wayne
The reason I didn't post this earlier was:
1. I have a probablem with using census statistics. After all he is trying to contact/emulate dead people. So the statistic we should look at are for older people, not the population at large.


Hi there! I'm not sure there is a good basis for saying this, Walter, since a good percentage of the spirit energies that come through belong to children and young people. :) .....neo

[Lurker]

Ah, finally Bill starts to answer some of the salient questiuons I have been asking for over two weeks!

Originally posted by BillHoyt


The definition of a Poisson distribution is based on that of a Poisson process. A Poisson process is one that satisfies the following:


1. The changes (or events) that result from the process can be grouped into nonoverlapping intervals.

2. The numbers of changes (or events) in the nonoverlapping intervals are independent from one another.

3. This independence holds for all intervals.

4. The probability of exactly one change (or event) in a sufficiently small interval, h = 1/n equals n*p , where p is the probability of one change (or event) and n is the number of trials.

5. The probability of more than one change (or event) in a sufficiently small interval, h, is essentially 0.

The Poisson distribution results when such a process occurs over n trials.

There are no hard and fast definitions to it, other than the above.

Lurker, you continue to insist that there is a question for me to answer about what one assumes when one derives Poisson from other distributions. This question makes no sense. The assumptions are grounded in the terms of those other distributions to derive Poisson, and are meaningless once you get to Poisson.

Poisson does not make an error when it predicts a p(x) beyond your n. The "n" is not in the Poisson distribution. Look closely at the definition above. "n" comes into play when you design your "bins" (the intervals). It affects your expected mean. Once you decide your expected mean, you have identified everything in Poisson. The "n" is now gone.

Bill, look at #1 through #5 again and pay particular attention to #4 and #5. Think about your sample size of 85. Consider the case where your sample size was 5 and the probability was 0.8.

Think about it Bill, Integrate your pdf to get your cdf for the range (0:5). When you complete this exercise, then the light may go on for you.

Lurker

[CFLarsen]

Originally posted by neofight
Hi there! I'm not sure there is a good basis for saying this, Walter, since a good percentage of the spirit energies that come through belong to children and young people. :) .....neo

Please point to those statistical analyses that show the age groups of "spirit energies" coming through.

Please either:

address the question, providing either a retraction or evidence of your claim, or
state that you refuse to answer.

[Thanz]

Originally posted by CFLarsen
Oh, I had an idea, that's all. That idea was not unfounded. Why do you want to shift the focus from you to me?
You did not have an idea. You simply copied BillHoyt. You do not actually KNOW what the questions you were asking meant. You simply wanted to harass me. Also, why do you want to shift the focus from you to me? We are discussing your lack of any ability to answer simple questions. I don't know why you keep bringing up my level of stats knowledge.

Did I make a claim? If so, what was it? If not, what right have you to demand an answer?
I asked because I thought you might have something to say about the topic, given your interest in the area of mediumship. You claim to know something about experimental design. You seem to claim that you are qualified to test JE to determine if he is a genuine medium. I am not sure why you think that you are qualified to do this, but have no idea how to count the number of J guesses in a transcript.

However, it appears I am mistaken. You do not want to answer my questions, probably because you do not want to go against BillHoyt and need to wait for him to tell you what to think. That's fine.

Oh, come off it! You were cornered on statistical issues, and now it's all my fault. Pluhease...!
No, I am simply pointing out the obvious:
1. You have not provided anything of value to this discussion.

2. You asked me a set of questions that you do not understand. Your motive seems to have been to harass me, as you would not understand the answers to the questions anyway.

Sure, go ahead with the personal attack, in the (vain) hope that your lacking statistical knowledge will not be noticed.
I am really not sure how my "lacking statistical knowledge" could NOT be noticed, considering that I have admitted the limits to that knowledge. I have, however, contributed positively to the discussion of this topic. I have performed the Poisson analysis to the count provided by Kerberos, and showed that on his count we could not reject the null hypothesis. I have done my own count of the J hits in Renata's JE LKL transcripts, and done the Poisson calculation on that count. On my count, we also cannot reject the null hypothesis according to the parameters set out by BillHoyt.

The only count that we can reject the null hypothesis is the count from BillHoyt. I have pointed out that Mr. Hoyt's counting procedure is not logical for the purposes of his test, and therefore his data is flawed.

What have you done? Nothing but harass me. When asked simple questions of logic, you hide. You are a poor skeptic, Mr. Larsen.

[BillHoyt]

Originally posted by Lurker
Ah, finally Bill starts to answer some of the salient questiuons I have been asking for over two weeks!
I have been answering. You still refuse to listen.
Bill, look at #1 through #5 again and pay particular attention to #4 and #5. Think about your sample size of 85. Consider the case where your sample size was 5 and the probability was 0.8.

Think about it Bill, Integrate your pdf to get your cdf for the range (0:5). When you complete this exercise, then the light may go on for you.

Lurker
N is not part of the distribution. Period. You have not found an error by finding probability beyond N. You simply make a laughable error. I am tired of saying it. YOU read my description and try to understand it this time.

[CFLarsen]

Thanz,

I did not want to "harrass" you. Please stop attributing motives to me I don't have.

I merely pointed out that you had no idea what you were asking BH about. Which was not all that far from the truth, was it?

If you feel I have "harrassed" you, I urge you to report me to the moderators, so we can clear this thing up. I, for one, would rather not have this serious accusation hanging over my head.

So, either report me, or stop crying about harrassment. Be true to your word or be a crybaby.

[Lurker]

Originally posted by BillHoyt

I have been answering. You still refuse to listen.

N is not part of the distribution. Period. You have not found an error by finding probability beyond N. You simply make a laughable error. I am tired of saying it. YOU read my description and try to understand it this time.

Integration will set you free, Bill. You DO know how to integrate, don't you?

Lurker

[BillHoyt]

Originally posted by Lurker


Integration will set you free, Bill. You DO know how to integrate, don't you?

Lurker

Laughingstock.

[Thanz]

Originally posted by CFLarsen
Thanz,

I did not want to "harrass" you. Please stop attributing motives to me I don't have.
Then what was your motive? The answers to the questions you were asking me would mean nothing to you. Actually getting the answers could therefore not be your motive.

[CFLarsen]

Originally posted by Thanz
Then what was your motive? The answers to the questions you were asking me would mean nothing to you. Actually getting the answers could therefore not be your motive.

I answered this already. I pointed out that you did not know what you were talking about. If you consider this "harrassment", well....:rolleyes:

I answered your question, please answer mine:

Have you reported me to the moderators for harrassing you?

[Thanz]

Originally posted by CFLarsen


I answered this already. I pointed out that you did not know what you were talking about.
You did not know anything about statistics yourself. Wasn't BillHoyt already posting in a similar vein? Doesn't he actually know something about statistics? Why did you not leave this for the "experts" as well? Why is it that you hide when asked to actually think for yourself?

I answered your question, please answer mine:

Have you reported me to the moderators for harrassing you?
No, and I'm not going to run and tell mommy either. :rolleyes:

[CFLarsen]

Originally posted by Thanz
You did not know anything about statistics yourself.

Not correct. I am not an expert on statistics, that's all.

Originally posted by Thanz
Wasn't BillHoyt already posting in a similar vein? Doesn't he actually know something about statistics? Why did you not leave this for the "experts" as well? Why is it that you hide when asked to actually think for yourself?

I don't know why BH does things. You really have to ask him about that. However, I did not detect anything wrong with what he was saying.

Which does not mean that he - or I - could be wrong. Which I have made clear before, too.

Originally posted by Thanz
No, and I'm not going to run and tell mommy either. :rolleyes:

Fine. Then stop complaining about being harrassed.

[Thanz]

Originally posted by CFLarsen

Not correct. I am not an expert on statistics, that's all.
Oh, so you DO know something about statistics? What do you know? Have you taken any courses? Did you understand the questions you were asking me? Would you have understood the answers to those questions? Can you do any statistical analysis yourself? Can you make any informed decisions about what statistical tools to use for a given situation?

I don't know why BH does things. You really have to ask him about that. However, I did not detect anything wrong with what he was saying.

Which does not mean that he - or I - could be wrong. Which I have made clear before, too.
But you were simply asking me questions that BillHoyt was already asking. Why bother repeating them? If you don't care about the answers (as you would not have understood them) why bother asking?

Fine. Then stop complaining about being harrassed.
No. If I think you are harrasing me, I'll say so.

[CFLarsen]

Thanz,

Do you have a problem regarding getting attention? Or do you have a Claus-fetish? You seem to want to provoke discussions with me, no matter what, even if no subject exists.

I've said what I want to say here. I haven't made any claims here (other that I am not an expert on statistics - how do I prove that? Easy...!).

Find another playmate to pick fights with. I prefer discussions of some intellectual merit. You merely bore me.

[Thanz]

Originally posted by CFLarsen
Do you have a problem regarding getting attention? Or do you have a Claus-fetish? You seem to want to provoke discussions with me, no matter what, even if no subject exists.
No, it is not about you, it is about discussing claims and the paranormal and research design. Things that you claim to be interested in. But refuse to actually answer questions about. If you won't share your knowledge, why are you posting here?

I've said what I want to say here. I haven't made any claims here (other that I am not an expert on statistics - how do I prove that? Easy...!).
No, you have claimed some positive level of knowledge of statistics. I am asking you to back that up with some details, so I know in the future what questions I can ask for your opinion on and what weight to give to that opinion. So, are you going to answer my questions about your claim that you know something about statistics?

Find another playmate to pick fights with. I prefer discussions of some intellectual merit. You merely bore me.
I tried to engage you in a conversation with intellectual merit. I asked for your contribution on test design and for a proper method of counting the JE guesses. You, despite what you say above, were not interested. Instead, you want to make long lists of questions to harass others with. You also need time to follow Clancie around the board so that you can disagree or pick apart anything she says.

Claus, I know that you feel that I am somehow not being fair with you. But all I did was ask for your input on the substantive content of the thread. It was something that you seemed perfectly willing to do when it consisted of buggin me about stats. But when asked to actually contribute something worthwhile, you clam up. You haven't even told me why my questions require "expertise" in the field of statistics.

You claim to be a skeptic. But you seem to be focussed on things other than an actual inquiry into the paranormal. If you can't "embarrass" some "believer", it seems that you lose interest rather quickly. I question your true motives.

[Lurker]

Bill:

I apologize. I seem to have been talking over your head. I will no longer mention integrals to you. It seems you fail to understand them.

Lurker

[BillHoyt]

Originally posted by Lurker
Bill:

I apologize. I seem to have been talking over your head. I will no longer mention integrals to you. It seems you fail to understand them.

Lurker

http://www.baltobluegrass.com/bbggraph/monkey.gif
Laughingstock.

[Thanz]

Originally posted by BillHoyt


The definition of a Poisson distribution is based on that of a Poisson process. A Poisson process is one that satisfies the following:


1. The changes (or events) that result from the process can be grouped into nonoverlapping intervals.

2. The numbers of changes (or events) in the nonoverlapping intervals are independent from one another.

3. This independence holds for all intervals.

4. The probability of exactly one change (or event) in a sufficiently small interval, h = 1/n equals n*p , where p is the probability of one change (or event) and n is the number of trials.

5. The probability of more than one change (or event) in a sufficiently small interval, h, is essentially 0.

The Poisson distribution results when such a process occurs over n trials.

There are no hard and fast definitions to it, other than the above.


Mr Hoyt -

I am still fuzzy as to why Poisson is appropriate for the analysis we are doing here. Could you perhaps specifically apply your general description of Poisson (quoted above) to the specific analysis we are doing here? What about the JE guesses makes you think it is a "Poisson Process"?

Much appreciated.

[Lurker]

Originally posted by BillHoyt

Laughingstock.

Hmm, when one looks around the room and notices that nobody else is laughing, a clueless person would continue laughing.

Lurker

[Lurker]

Show me the math, Bill. It is a rather simple request, is it not?

Lurker

[BillHoyt]

Originally posted by Lurker


Hmm, when one looks around the room and notices that nobody else is laughing, a clueless person would continue laughing.

Lurker

If you don't hear the derisive laughter, Lurker, I suggest Q-tips.

[T'ai Chi]

Around 20 pages after statistics were being talked about, and still no appropriate statistical analysis has been done of the JE counts.

Think some of the JREF board participants focus a little too much on rhetoric?

Nah!:k:

[BillHoyt]

Originally posted by T'ai Chi
Around 20 pages after statistics were being talked about, and still no appropriate statistical analysis has been done of the JE counts.

Think some of the JREF board participants focus a little too much on rhetoric?

Nah!:k:

This from one who insists on exhaustive induction? Righhhhht.

[Lurker]

Bill,

Yes, I hear you laughing. Well done! Very good response. Now, when you finish laughing at my ineptitude, could you kindly show me your calculations on the problem I proposed?

Thanks!

Lurker

[Thanz]

Mr. Hoyt -

Will you be answering my question regarding the applicability of Poisson to the present analysis?

[BillHoyt]

Originally posted by Thanz
Mr. Hoyt -

Will you be answering my question regarding the applicability of Poisson to the present analysis?

I tire of answering the same question over and over again. Please have somebody explain my answer to you.

[Lurker]

Bill:

For me, all you have to do is a simple math exercise. As per your limitations, I promise there will be no integrals.

Lurker

[Thanz]

Originally posted by BillHoyt


I tire of answering the same question over and over again. Please have somebody explain my answer to you.
You know, I would ask someone else, but you are the only one who is advocating the use of Poisson. It was you who used Poisson for your analysis. I am trying to understand why.

I do not think that you have actually answered this question once, let alone "over and over again". I know that you don't think Poisson is "Binomial lite", and I know that you don't think that there is enough data for a chi square.

What I don't know is why JE guesses would be a Poisson process. Since it is your claim that Poisson is appropriate in this analysis, I must ask you to back up that claim and explain why.

I am sincerely trying to understand why you have used this particular analysis.

[BillHoyt]

Originally posted by Lurker
Bill:

For me, all you have to do is a simple math exercise. As per your limitations, I promise there will be no integrals.

Lurker

I told you the error. Poisson is not parameterized by N. The error is yours. Have somebody else explain this to you. Take a course. Whatever you need to get up to speed.

[Lurker]

Bill, take the same problem you did in your "J" analysis. Change the p to 1.0. Apply that to the census data. Your expected value for the 85 is 85 right? Does Poisson predict this? Show the CDF.

Try again for p=0.9. Again for p=0.8.

Remember, same problem. All we have changed is the p from the census.

Do the math, Bill. Why are you afraid to do the math?

Lurker

[BillHoyt]

Originally posted by Lurker
Bill, take the same problem you did in your "J" analysis. Change the p to 1.0. Apply that to the census data. Your expected value for the 85 is 85 right? Does Poisson predict this? Show the CDF.

Try again for p=0.9. Again for p=0.8.

Remember, same problem. All we have changed is the p from the census.

Do the math, Bill. Why are you afraid to do the math?

Lurker

I told you the error. Poisson is not parameterized by N. The error is yours. Have somebody else explain this to you. Take a course. Whatever you need to get up to speed.

[neofight]

Originally posted by CFLarsen
Thanz,

Do you have a problem regarding getting attention? Or do you have a Claus-fetish? You seem to want to provoke discussions with me, no matter what, even if no subject exists.

I've said what I want to say here. I haven't made any claims here (other that I am not an expert on statistics - how do I prove that? Easy...!).

Find another playmate to pick fights with. I prefer discussions of some intellectual merit. You merely bore me.

:roll: OMG, this never-ending pot calling the kettle black nonsense is too much to take at times! rofl Oh the irony of it all! Claus, sometimes you are sooooo funny. Guffaw! Especially when you are not at all aware of it. :roll: .....neo

[Lurker]

Bil, Bil, Bill:

Still afraid to do the math? Show me the math. You continue to avoid the question. Do the math. p=1.0, 0.9, 0.8.

Do the exact same "J" analysis and use p as above and apply to your expected mean and your census data (which is how you got the p in the first place).

Do science a favor and do the math and quit ducking. You are giving us science people a bad name here.

Lurker

[BillHoyt]

Originally posted by Lurker
Bil, Bil, Bill:

Still afraid to do the math? Show me the math. You continue to avoid the question. Do the math. p=1.0, 0.9, 0.8.

Do the exact same "J" analysis and use p as above and apply to your expected mean and your census data (which is how you got the p in the first place).

Do science a favor and do the math and quit ducking. You are giving us science people a bad name here.

Lurker

:bs:

[Lurker]

Originally posted by BillHoyt


:bs:

I am trying to teach you something here, Bill. Why don't you just do the math. Or explain how the problem is ANY different than what you did.

Thanks,

Lurker

[Lurker]

There are two sides here. One side wants to repeat the same problem with a different value of p. The other side refuses to try the exercise.

You tell me which you think represents the skeptical philosophy better?

In my opinion, Bill, you are starting to look a lot like Gary Schwartz.

Lurker

[Thanz]

Originally posted by Lurker
Bill, take the same problem you did in your "J" analysis. Change the p to 1.0. Apply that to the census data. Your expected value for the 85 is 85 right? Does Poisson predict this? Show the CDF.

Try again for p=0.9. Again for p=0.8.

Remember, same problem. All we have changed is the p from the census.

Do the math, Bill. Why are you afraid to do the math?

Lurker
I'll do some math!

I can calculate the expected number for our sample of 85, but I don't know what number you want me to use for the observed number of events. Are we using 17 still?

[Lurker]

Originally posted by Thanz

I'll do some math!

I can calculate the expected number for our sample of 85, but I don't know what number you want me to use for the observed number of events. Are we using 17 still?

Thanz:

I must admit I am a bit flummoxed by Bill. I have tried being nice. I have tried being snide. I have tried being damn annoying. For someone who seems to pride himself on being a skeptic he sure dodges simple questions.

As to the problem, the 17 count is immaterial. For p=0.9, and using the 85 sample size, what is the probability of getting 85 or less?

Simple. Why won't Bill show the math?

Lurker

[Thanz]

Originally posted by Lurker
Thanz:

I must admit I am a bit flummoxed by Bill. I have tried being nice. I have tried being snide. I have tried being damn annoying. For someone who seems to pride himself on being a skeptic he sure dodges simple questions.

As to the problem, the 17 count is immaterial. For p=0.9, and using the 85 sample size, what is the probability of getting 85 or less?

Simple. Why won't Bill show the math?

Lurker
Well, I have done the math. I'm prepared to post it if you are interested or if you think it will move the discussion along.

[T'ai Chi]

Say JE uses J more than expected. BUT, what if JE also uses some of the other high frequency letters less than expected?

Could we say anything meaningful here?

[BillHoyt]

Originally posted by T'ai Chi
Say JE uses J more than expected. BUT, what if JE also uses some of the other high frequency letters less than expected?

Could we say anything meaningful here?

I thought you were a statistician. An astounding question. How about you spin some hypotheses. You might even answer one of the naive questions that has haunted some of the woos on this thread.

[Thanz]

Originally posted by BillHoyt
There are three choices as I see them: drop such guesses entirely and thereby lose most of the data, pick one letter and run with it (but which one?) or make a uniform rule allowing him as much leeway as you can. I said I tried to honor his process as much as possible, and I decided to grant him the leeway. The specific leeway I did not grant was "Rich or Richard", where one is clearly a nickname for the other. In those cases, I counted one guess. If he said "Rich or Richard or R" I counted two guesses.

I am quoting this again because I do not think that you have provided any logical basis for your counting method. You have adequately explained what the counting method was, but not the logical reason behind it.

Specifically, WHY is it appropriate to count "Rich or Richard or R" as two separate guesses of "R"? He is clearly guessing for ONE person, not two, and hoping that he gets a hit close to richard. If they say "Randy" he will still accept it as a hit. But either way, he is just casting ONE R net here for ONE person.

The comparison we are doing is to the census data, which obviously counts people. Should we not also be counting people in the guesses, rather than just names? Isn't it obvious in this example that JE is referring to only one person?

Your count is inaccurate and inappropriate to be used in a comparison to the census data. Unless you think the census counts people more than once.

[BillHoyt]

Originally posted by Thanz
The comparison we are doing is to the census data, which obviously counts people. Should we not also be counting people in the guesses, rather than just names? Isn't it obvious in this example that JE is referring to only one person?

What is obvious is that JE calls for a person with a spice name and accepts a dog's name as an answer. What is obvious is that JE sometimes calls out the same initial and states there are two people by that name. What is also obvious is that his multiple guesses are difficult to tally in a regularized way. I chose a rule that would cover the most cases: count all names cited unless one is clearly a nickname of another. This rule covers JE in cases where he guesses "Ellen, Helen, or some 'L' name" and it covers "Richard or some 'R'" name. You may disagree with the method, but I have explained it. Again.

[Clancie]

So, Bill, if JE said to you, "I'm getting someone with a 'B' name, like Bob, Bill, Ben" you would count that as four guesses for 'B'.

And that counting method makes sense to you. :eek:

(Also, as I've said before, "Ginger" shouldn't count at all, btw, since JE got the name symbolically, not phonetically).

Oh well. Just another example of a "skeptic" who is unwilling to admit when he's wrong. :rolleyes:

[Thanz]

Originally posted by BillHoyt


What is obvious is that JE calls for a person with a spice name and accepts a dog's name as an answer.
So what? We shouldn't count nicknames anyway as they are not part of the census.
What is obvious is that JE sometimes calls out the same initial and states there are two people by that name.
And in those cases we count two guesses. Not hard.
What is also obvious is that his multiple guesses are difficult to tally in a regularized way.
Difficult, maybe. But not impossible. Re-read my method and tell me where the flaws are, if you can.
I chose a rule that would cover the most cases: count all names cited unless one is clearly a nickname of another. This rule covers JE in cases where he guesses "Ellen, Helen, or some 'L' name" and it covers "Richard or some 'R'" name. You may disagree with the method, but I have explained it. Again.
The only reason you picked it is because it is easy? Even though you know that it is incorrect?

Let's look at it from another angle. What are we trying to determine? We are trying to determine whether or not JE is cold reading. We have theorized that JE will guess higher frequency letters more often as they increase the chance of a hit. What we are concerned with is how much JE's methods seem directed to increasing his chance of a hit. The way that he does this is by casting as wide a net as possible.

One way to cast a wide net is to guess high frequency letters. Another is to guess multiple names. When we look at the data, we see that he rarely guesses multiple names that are dissimilar from one another. He does not say "Bob or John or Peter". he will say "Peter or some P name". In this instance, saying "Peter" does nothing to increase his chances of a hit (a hit of Peter will already be covered in "P"), it only makes him seem better if the P name IS Peter. If we are simply looking at frequency of letters, it makes no sense to count "Peter" and "P" as two separate and distinct guesses of the letter "P". They are not. It is only one "P" guess for one person.

Frequently this occurs when JE will guess a name like Peter, get nothing, and expand his guess to any P. It is still one P guess, not two, as he is still guessing for one person.

As for the Ellen/Helen, or J or G name, I counted each of those as 2, as he is attempting to widen the guess net beyond just one letter.

My method is also easy to apply, and it yields, IMO, a more accurate count for our purposes. Can you make any argument, beyond "Ease" for your method? Specifically, can you make any argument that it is more accurate?

[BillHoyt]

Thanz,

First post out of the box in reply to me and already you distort my post? Where did I say "ease" or "easy"? Would you care to try again or do you just wish to push an agenda?

[CFLarsen]

Originally posted by Clancie
So, Bill, if JE said to you, "I'm getting someone with a 'B' name, like Bob, Bill, Ben" you would count that as four guesses for 'B'.

And that counting method makes sense to you. :eek:

Do you have a better solution?

Originally posted by Clancie
(Also, as I've said before, "Ginger" shouldn't count at all, btw, since JE got the name symbolically, not phonetically).

Why not? Ginger is a name, such as Mary and Deborah. How do you know when JE gets a name symbolically? What's the symbol for "Eula"??

Originally posted by Clancie
Oh well. Just another example of a "skeptic" who is unwilling to admit when he's wrong. :rolleyes:

Perhaps you could spare us your personal dislikes and instead try focusing on the issues.

[Thanz]

Originally posted by BillHoyt
Thanz,

First post out of the box in reply to me and already you distort my post? Where did I say "ease" or "easy"? Would you care to try again or do you just wish to push an agenda?
Well, if the reason is not ease of applicability, then what is it? That is what I got out of your post. If it is something else, let me know.

[Thanz]

Originally posted by CFLarsen


Do you have a better solution?
I do. And I have posted it a couple of times.

Why not? Ginger is a name, such as Mary and Deborah. How do you know when JE gets a name symbolically? What's the symbol for "Eula"??
Personally, I don't car about getting it symbolically. It should be ignored because it is a nickname, and nicknames are not part of the control census data. From Renata's thread:

CALLER: Hello?
EDWARD: Hello.
KING: Hello.
CALLER: Good. How are you doing, John?
EDWARD: I'm doing good.
CALLER: Good. I'm just seeing if you can connect with anything?
EDWARD: The first thing -- actually, a couple of things. Somebody's got a nickname after a spice, like pepper?
CALLER: I'm sorry?
EDWARD: Somebody has a nickname after a spice, like pepper? Who's got a spice name?
CALLER: Spice name? Don't know.
EDWARD: Salty or pepper, cinnamon.
CALLER: Oh, my dog.
EDWARD: OK. What's the name?
CALLER: Her name is Ginger.

[CFLarsen]

Originally posted by Thanz
I do. And I have posted it a couple of times.

I asked Clancie.

Originally posted by Thanz
Personally, I don't car about getting it symbolically. It should be ignored because it is a nickname, and nicknames are not part of the control census data. From Renata's thread:

Animals have nicknames and not names? I would never ask someone "What's your dog's nickname?"

Would you?

[Thanz]

Originally posted by CFLarsen


I asked Clancie.
Why do you care what she thinks about this? You don't even have any thoughts on it yourself.

Animals have nicknames and not names? I would never ask someone "What's your dog's nickname?"

Would you?
No, it is not the fact that it is a dog. It is the fact that JE says he is bringing through a nickname. Read the transcript - he is not guessing a name, he is guessing a nickname. I even bolded it for ease of reference.

[T'ai Chi]

Thanz is correct here on this point. JE is clearly talking about a nickname and not a proper name.

[Loki]

You can't count "Ginger" as a guess, because JE didn't make that guess. "Ginger" is the answer, not the guess.

If JE said "Whos the relative named after a film star" and the sitter replied "Arnold". then this isn't a guess against "A".

[CFLarsen]

Originally posted by Thanz
Why do you care what she thinks about this? You don't even have any thoughts on it yourself.

She complains that BillHoyt's suggestion isn't good enough. Therefore, she must have thought of something better. If she hasn't, then she merely wants to prevent such an analysis, by pooh-pooh'ing everything that comes up.

I ask because I want to find a solution. Do you have a problem with that, Thanz? Why don't you have a problem with Clancie not presenting her own view (she must have one)?

Originally posted by Thanz
No, it is not the fact that it is a dog. It is the fact that JE says he is bringing through a nickname. Read the transcript - he is not guessing a name, he is guessing a nickname. I even bolded it for ease of reference.
Yeah, but I'm a bit uneasy with it being a dog - and a living one, too. You see, I fail to see where in JE's "process" he can talk to living animals...unless it's the sitter that makes this fit. Then, JE has no problems accepting that it's an animal.

Red Flag Rising.

[BNiles]

I agree. What ever process JE uses, if he can tell "symbolicly" between male or female, father figure or mother figure, I'm sure he should be able to extract the difference between Homosapien and Canine.

[Thanz]

Originally posted by CFLarsen
I ask because I want to find a solution. Do you have a problem with that, Thanz? Why don't you have a problem with Clancie not presenting her own view (she must have one)?
If you look back in the thread - to page 19 - you will see that Clancie has already posted her own view that "I'm getting a J name like Jenny, John, Joan" is one guess, Bill, only one 'J' name.

I am glad that you want to find a solution. Do you have any thoughts that might actually help us come to a solution? I have posted my view, Clancie has posted hers, and Bill started the ball rolling. He has failed to defend the accuracy of his count, however.

But you, Claus, have been silent on the matter. If you want to find a solution, why not at least post something substantive on the topic? How would you count the guesses?

Yeah, but I'm a bit uneasy with it being a dog - and a living one, too. You see, I fail to see where in JE's "process" he can talk to living animals...unless it's the sitter that makes this fit. Then, JE has no problems accepting that it's an animal.
I'm not crazy about this either, but that is really a different topic. We can, and do, discuss the various "hits" of JE to death. What we are trying to do with this stats stuff is get an accurate count of his name guesses to compare them to the census. As this is not a proper name guess (either by guessing a letter or by guessing for a proper name that would be included in the census) it should not be part of the count.

[CFLarsen]

Nice try. I've already said what my stance is.

[Thanz]

Originally posted by CFLarsen
Nice try. I've already said what my stance is.
Yes - you'll "wait for the experts". Because you don't know how to count, I guess.

If that is your stance, don't criticize others for not doing what you refuse to do. Especially when you are wrong and they have already done it.

[BillHoyt]

Originally posted by Thanz
If you look back in the thread - to page 19 - you will see that Clancie has already posted her own view that ...
Yes, she has. But her view doesn't help the problem with JE's guesses. Sometimes he gives multiple names, apparently identifying a single person. Sometimes he gives a single name and clearly states that he is identifying two people. Sometimes he says "nickname" for a person and ends up identifying a dog's name (not "nickname").

My solution is to make the fewest assumptions about his process or intent and to simply count the separate guesses. Where he gives a combination of name and its corresponding nickname, I collapse those into a single guess.
I am glad that you want to find a solution. Do you have any thoughts that might actually help us come to a solution? I have posted my view, Clancie has posted hers, and Bill started the ball rolling. He has failed to defend the accuracy of his count, however.
Get your facts straight. I didn't start the ball rolling. I have defended the accuracy.
I'm not crazy about this either, but that is really a different topic. We can, and do, discuss the various "hits" of JE to death. What we are trying to do with this stats stuff is get an accurate count of his name guesses to compare them to the census. As this is not a proper name guess (either by guessing a letter or by guessing for a proper name that would be included in the census) it should not be part of the count.
In this case, JE said "nickname" and he said "name". It turned out to be a dog, not a person. It turned out to be the dog's name, not its nickname. JE specifically said "salty", "pepper" and "cinnamon" as the name guesses. And here, please get your facts straight again. 1. The name guesses do not have to be in the census. 2. "Pepper" and "Cinnamon" are both people's names. In the U.S., they are usually girl's names. Although "Pepper" has also been used as a man's nickname. 3. The dog's actual name, "Ginger", was not counted as a JE guess and is also a female (human) surname.

Cheers,

[Clancie]

Posted by Thanz

If you look back in the thread - to page 19 - you will see that Clancie has already posted her own view
Yes, Thanz. And more of my views on tallying are on page. 18, too.


What we are trying to do with this stats stuff is get an accurate count of his name guesses to compare them to the census.
Yes, and did Bill ever answer T'ai Chi's question about tallying other letters, too?

And...the new book adds this to the mix:
"After Life" p.80

"...For me when I hear names that start with a vowel, I will not hear that first vowel. I'll hear the consonant sounds following that vowel as strong and predominant. So in this case "Elan" becomes more of a "Lan" or "Lin" sound in my head because I didn't hear the "E" sound."

[Clancie]

Posted by Bill Hoyt

Yes, she has. But her view doesn't help the problem with JE's guesses.
Actually, Bill, if you read page 18-19, my count answers all those questions just fine. In fact three of us used pretty much the same method and got pretty much the same results.

Your results were way off of what everyone else got--with a much more inflated number of overall "guesses" and an artificially inflated number of "J's".
Sometimes he gives multiple names, apparently identifying a single person.
This has been addresses. No problem. (And no need to count, "I'm getting a 'J' like Joseph, John, Jim..." as four guesses of 'J'. It's one 'J' guess, Bill, one 'J' name matched with one person.
Posted by Bill Hoyt

Sometimes he give a single name and clearly states that he is identifying two people.
In which case, as someone else said, we count it as two guesses on 'J'. (It only happened once in these transcripts, btw, not a big deal--unless he says, "I've got two men with 'J' names...like Joseph, John, Jim..." and we count it as 8 separate guesses for 'J' which would be your method. :eek:
Posted by Bill Hoyt

Sometimes he says "nickname" for a person and ends up identifying a dog's name (not "nickname").
He got "spice name" symbolically, not phonetically. So by my rules...it's out of the count. Consistent. Simple.

[Lurker]

I had presumed that Bill would tally the letters and guesses fairly and objectively. I do understand his point that he IS trying to be objective by including all names as seperate guesses. Thus, for a non-"J" name the multiple guesses work against supporting his "J" analysis results.

But I don't think he needed to do that. I think he could safely assume that each string of names was for one person, not new guesses.

And according to what others have said here, this simple understanding would change the results dramatically.

Interesting.

Lurker

[BNiles]

Originally posted by Clancie
He got "spice name" symbolically, not phonetically. So by my rules...it's out of the count. Consistent. Simple. [/B]

My turn to agree with Clancie on this one. If we're counting name to letter guesses as compared the census then this guess shouldn't be considered because he didn't specify a letter.
Now if we have a census of common spice names we could compare it to that. ;)

Also note that this shouldn't be considered a hit either. It's obvious to me that JE was fishing for this one. (Who am I kidding? He fishes for all of them.:D )

[Thanz]

Originally posted by BillHoyt

Yes, she has. But her view doesn't help the problem with JE's guesses. Sometimes he gives multiple names, apparently identifying a single person. Sometimes he gives a single name and clearly states that he is identifying two people. Sometimes he says "nickname" for a person and ends up identifying a dog's name (not "nickname").
All of these situations are easily accounted for in the method I have proposed.

One person, one letter = one guess, regardless of how many specific names he guesses. The net is only as wide as one letter.

Two persons, one letter = two guesses.

One person, two letters = two guesses. He is trying to widen the net to get a hit, like a cold reader does.

Nicknames - not part of our control data, therefore don't count. Treat this guess like a guess of a feather, or a calendar, or whatever.

My solution is to make the fewest assumptions about his process or intent and to simply count the separate guesses. Where he gives a combination of name and its corresponding nickname, I collapse those into a single guess.
The problem is, they are NOT separate guesses. "Bob or Bill or some B name" is one guess, with the net as wide as "B", and a couple of specifics hoping for a better hit.

Your method equates two readings where he says "I am getting a J connectoin" with one reading where he states "I am getting a "John" or "J" connection here". I do not agree that those are the same situation. My method counts them differently, yours counts them the same. And that is why your method is inaccurate.
Get your facts straight. I didn't start the ball rolling. I have defended the accuracy.
By "Get the ball rolling" I meant that you were the first to post your counting method. I suppose Kerberos did a count before you. Not that it really matters.

Also, you have not defended its accuracy. You have simply defended its ease of applicability to multiple situations. However, by equating these multiple situations as explained above, you are making your count inaccurate.

In this case, JE said "nickname" and he said "name". It turned out to be a dog, not a person. It turned out to be the dog's name, not its nickname. JE specifically said "salty", "pepper" and "cinnamon" as the name guesses.
As nickname guesses, not part of what is in our control data.

1. The name guesses do not have to be in the census.
Why not? The census is our control data. If nicknames don't appear there, they would not be counted, and we don't know what kind of distribution of letters of nicknames there might be. If you include nicknames, why not place names or object names as well?
2. "Pepper" and "Cinnamon" are both people's names. In the U.S., they are usually girl's names. Although "Pepper" has also been used as a man's nickname.
So what? He said that he was bringing through a NICKNAME. Something that would not be counted in the census, and therefore not part of the control data. The person with the spicy nickname would have a regular name as well, and that is the name that would be counted.

Also, counting a name guessed in this manner does not fit in with our overall theory. Our theory is that he will guess more popular letters at the expense of less popular letters. Here, he is not guessing a letter at all, rather, he is guessing some other sort of grouping.
3. The dog's actual name, "Ginger", was not counted as a JE guess and is also a female (human) surname.
That's fine. Especially considering, as I think Claus pointed out, it was supplied by the sitter not JE.

Now, I have explained my counting methods several times, including why I think it is more accurate. If you disagree, I would like to know why. What, specifically, makes my counting method inaccurate? What makes your counting method more accurate than mine?

[BillHoyt]

Originally posted by Thanz
All of these situations are easily accounted for in the method I have proposed.
Really?

One person, one letter = one guess, regardless of how many specific names he guesses. The net is only as wide as one letter.

Two persons, one letter = two guesses.

One person, two letters = two guesses. He is trying to widen the net to get a hit, like a cold reader does.[/b]
Nice until you realize the guesses don't always correspond to people. And then you realize he doesn't specify how many people he is calling for, except for that one time he specifically said "two". Then you look closer and see him accepting dog's names. And then last names. Read on...

Nicknames - not part of our control data, therefore don't count. Treat this guess like a guess of a feather, or a calendar, or whatever.
Out go all the "C", "K", "J", "M", "R", etc guesses, too. None of those are in the census data.

The experiment does not require the name be in the census data. The census data simply sets up our expected mus for each letter bin.

The problem is, they are NOT separate guesses. "Bob or Bill or some B name" is one guess, with the net as wide as "B", and a couple of specifics hoping for a better hit.
Except when it isn't. When it refers to a last name. Or a dog's name. Or to two people. Or...

Your method equates two readings where he says "I am getting a J connectoin" with one reading where he states "I am getting a "John" or "J" connection here". I do not agree that those are the same situation. My method counts them differently, yours counts them the same. And that is why your method is inaccurate.
Huh?
By "Get the ball rolling" I meant that you were the first to post your counting method. I suppose Kerberos did a count before you. Not that it really matters.
Really? Read Clancie's claims. The previous results also refuted the null hypothesis.

Also, you have not defended its accuracy. You have simply defended its ease of applicability to multiple situations. However, by equating these multiple situations as explained above, you are making your count inaccurate.
I have said before "ease" has nothing to do with it. It has to do with counting consistency. I set the counting rules to match JE's actions.

As nickname guesses, not part of what is in our control data.
You need to understand the experiment is based on letter-bins. The census data sets up the expected mus. Period.

[Thanz]

Originally posted by BillHoyt

Really?
Yep.
Nice until you realize the guesses don't always correspond to people. And then you realize he doesn't specify how many people he is calling for, except for that one time he specifically said "two". Then you look closer and see him accepting dog's names. And then last names. Read on...
When he makes them they do. When he says "I'm getting an "R" connection here..." he is guessing a name. It makes NO DIFFERENCE whatsoever how, or if, the sitter validates. We are counting his guesses, not his hits. So unless he specifies that he is getting a nickname, a dog, or a last name, we can safely assume that he is guessing a normal first name - as that is what he usually does. And if he specifically says "two" it is two guesses. If he doesn't, he is hoping for one hit. It is one guess.

Out go all the "C", "K", "J", "M", "R", etc guesses, too. None of those are in the census data.
Of course they are in the census data. What are you talking about? How else do we get 13.36% for J of this information is not in the census data? They count all the names. They don't count any nicknames. Get it?

The experiment does not require the name be in the census data. The census data simply sets up our expected mus for each letter bin.
That's right, it does. But we DON'T have any expected mus for NICKNAMES, as the census doesn't count them. Therefore, we shouldn't count them.

Except when it isn't. When it refers to a last name. Or a dog's name. Or to two people. Or...
Again, we are counting guesses, not hits. In this analysis, the hits are not relevant. Therefore, when he says "J connection" we count a guess. We still count a guess if the sitter validates it as a last name instead of a first name. What is important is the guess, not the sitter's response.

Huh?
Let's make this a concrete example:

Reading 1:
JE: I am getting a "J" connection here.
Sitter: J?
JE: Yes, a "J" - like John, or Joe
sitter: I had an uncle Joe....

My method: one J guess.
BillHoyt:3? 4? J guesses?

Reading 2
JE: I am getting a "J" connection..
Sitter: My grandfather was John

Thanz:1 J
BillHoyt:1 J

Reading 3:
JE: I am getting a "Jim" connection here...
Sitter: Nope, I don't know any Jim
JE:What is the Canada connection?
Sitter: Blah blah

Thanz: 1 J
BillHoyt: 1 J

Reading 4
JE: I am sensing an older female
Sitter: My Mother has passed
JE: was her name "Jennifer"
Sitter: no, it was Roberta

Thanz: 1 J
Bill Hoyt: 1 J

Now, here is my problem with your counting method. In your method, reading 1 has as much weight as readings 2, 3, and 4 combined. However, in all cases, he is trying to make one J connection. Remember, we are trying to count how many times he will guess a certain letter, for cold reading purposes. If we have 3 separate readings (2, 3, 4) in which he makes a "J" guess, that is much different than the one reading with the multiple names. That distinction is lost in your method. My method counts all of them equally.

Really? Read Clancie's claims. The previous results also refuted the null hypothesis.
I am not sure what you mean by "read Clancie's claims".

Also, the previous results did not refute the null hypothesis, as I have already posted. Kerberos did a different analysis on the data. But if we take HIS raw counting numbers, and apply YOUR hypothesis to them, the null hypothesis cannot be rejected. The same thing happens with my count. The only count that rejects the null hypothesis is your flawed count.

I have said before "ease" has nothing to do with it. It has to do with counting consistency. I set the counting rules to match JE's actions.
My rules are just as consistent, and more accurate for our purposes.

You need to understand the experiment is based on letter-bins. The census data sets up the expected mus. Period.
I understand that perfectly. Nicknames, as they are not part of the census, are not part of setting up those expected mus. We have no idea what the expected mus would be for nicknames as opposed to proper names, so we should not count them.

[BillHoyt]

Originally posted by Thanz
Also, the previous results did not refute the null hypothesis, as I have already posted. Kerberos did a different analysis on the data. But if we take HIS raw counting numbers, and apply YOUR hypothesis to them, the null hypothesis cannot be rejected. The same thing happens with my count. The only count that rejects the null hypothesis is your flawed count.

Thanz,

What? Sorry, this is so far from right, you'll need a plane ticket to get back. The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?

[Thanz]

Originally posted by BillHoyt

What? Sorry, this is so far from right, you'll need a plane ticket to get back. The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?
Huh? Kerberos did an analysis that combined a bunch of the less frequently used letters. In order to do this, he had to count the number of guesses for each letter. His count was 14 J guesses out of a total of 78 (page 5 of this thread).

Your analysis was only of the letter J. You also had to count the number of letter guesses, but strictly speaking you did not have to keep separate totals for any letter other than J. Your count was 18 J guesses out of a total of 85. You used Poisson, and found that the probability of >= 18 was about .03, which rejected the null hypothesis.

If we apply Poisson to the numbers in Kerberos count, with an expected count of 10.42 and an actual count of 14, the probability of >= 14 is .168, which means that the null hypothesis cannot be rejected. I already posted this on page 19.

I also posted my count, 9 of 43, .128 - no rejection of null hypothesis.

I am simply applying your analysis to data collected by others, as I see your data collection as inaccurate. Is there some reason why I should NOT be able to apply your analysis to the raw data collected by Kerberos? He was counting the same thing - letter guesses. He just wanted to do a different analysis of them. That doesn't change the raw data he collected.

[BillHoyt]

Thanz,

Take II:

The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?

[Thanz]

Originally posted by BillHoyt
Thanz,

Take II:

The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?
Your reply was very quick, so I do not know if you have read my reply or not.

Quite simply, Kerberos did a different analysis with different control data (juninho's member distribution). I do not know what stat tools he used to come up with his analysis. My gut feeling (that I have expressed many times) is that the sample is too small to do the kind of combining that he has done.

However, I do not want to get into a debate regarding whether his method is valid or not. We got into this by me saying there was not enough data, and you insisted that there was - depending on what test you want to do. You then proposed a test that you insist has meaning to determine whether JE is cold reading. That test involves comparing the number of times that the letter J is guessed by JE to the general population proportion of J guesses. You were very specific in your formation of the hypothesis and null hypothesis:

I would frame the hypothesis that JE is cold-reading and his "J" guesses will show this by being significantly more frequent than chance alone would dictate. The next step is to turn this hypothesis on its head. This is called the "null hypothesis", and it would look like this: JE is not cold-reading and his "J" guesses will not be significantly higher than chance alone would dicatate Then I would select the significance level, probably .05 and look up the one-tailed test for significance. Why one-tailed? Because of how I framed the null hypothesis: I'm only interested in how unlikely it is to have had this high a number assuming his guesses were really random.
It seems to me that your null hypothesis is very specific, and not the same as Kerberos.

What I have done, is taken YOUR hypothesis and null hypothesis that you proposed as having real meaning for our purposes, and your preferred statistical tool (Poisson) to data collected by others. And we have seen the results. The only data that rejects YOUR specific null hypothesis is the flawed data you collected.

[BillHoyt]

Originally posted by Thanz

Your reply was very quick, so I do not know if you have read my reply or not.

Thanz,

The essential null hypothesis here is that JE is cold reading. The choice of Js or Ks or groups of low-frequency initials is not integral to the hypothesis. How we choose to do the comparison to corroborate or refute the null hypothesis does not alter the null hypothesis.

Kerberos' approach rejected the null hypothesis of cold reading. My approach rejected the null hypothesis of cold reading.


:rolleyes:

[BillHoyt]

Take III:

The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?

[Thanz]

Originally posted by BillHoyt
Kerberos' approach rejected the null hypothesis of cold reading. My approach rejected the null hypothesis of cold reading.
Kerberos' approach, which hasn't really been analytically dicussed herre (we don't know what stats tools he used, or whether they were appropriate) rejected the null hypothesis of cold reading based on DIFFERENT CONTROL DATA.

You were very specific in your formulation of the null hypothesis. It was italicized. You kept repeating that your analysis just rejected the null hypothesis. It did not rule out any other factors. It did not tell us anything about rare letters. It just told us about the J.

Further, your analysis only rejects the null hypothesis of cold reading when your flawed counting method is used to collect the data. How do you keep missing this point? Your data is flawed, and therefore we cannot trust your result. When ANY OTHER count posted here is used, your analytical approach DOES NOT reject the null hypothesis. This is the point I am making, and you keep avoiding. It doesn't matter what Kerberos test says - we are talking about your very specific null hypothesis.

[Thanz]

Originally posted by BillHoyt
Take III:

The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?
As I have tried to point out, ad nauseum, it simply does not matter. Your question is irrelevant. It makes no difference whether Kerberos even had a null hypothesis, whether it was the same or different. I am just using his raw counting data. Get it? Understand? Will you now address the actual substantive issues here?

To recap:
1. Your counting method is inaccurate, for the reasons posted above and not addressed by you.

2. If your raw data is incorrect, your analysis cannot be trusted to be correct.

3. If we use the raw data collected by anyone else, and apply your test to it, the null hypothesis cannot be rejected.

[BillHoyt]

Originally posted by Thanz

Kerberos' approach, which hasn't really been analytically dicussed herre (we don't know what stats tools he used, or whether they were appropriate) rejected the null hypothesis of cold reading based on DIFFERENT CONTROL DATA.

You were very specific in your formulation of the null hypothesis. It was italicized. You kept repeating that your analysis just rejected the null hypothesis. It did not rule out any other factors. It did not tell us anything about rare letters. It just told us about the J.

Further, your analysis only rejects the null hypothesis of cold reading when your flawed counting method is used to collect the data. How do you keep missing this point? Your data is flawed, and therefore we cannot trust your result. When ANY OTHER count posted here is used, your analytical approach DOES NOT reject the null hypothesis. This is the point I am making, and you keep avoiding. It doesn't matter what Kerberos test says - we are talking about your very specific null hypothesis.

Any Newfs in your area? They usually respond to the sounds of arms flailing on the water.

The data have nothing to do with the hypothesis. The control data have nothing to do with the hypothesis. The specific analyses have nothing to do with the hypotheses.

This is fundamental to understanding experimental design.

[BNiles]

Originally posted by BillHoyt
Take III:

The null hypothesis is different from the experimental method. Do you understand that? Do you understand that the Kerberos null hypothesis and mine are the same?

Does this mean that neither you nor Kerberos were doing the "experimental method"? And if you and Kerberos are doing the same "null hupothesis", why two different answers?
Kerberos = .168
BillHoyt = .03
This seems like a big diffence to me. Could it be your counting method?
:confused:

[BillHoyt]

Originally posted by Thanz

As I have tried to point out, ad nauseum, it simply does not matter. Your question is irrelevant. It makes no difference whether Kerberos even had a null hypothesis, whether it was the same or different. I am just using his raw counting data. Get it? Understand? Will you now address the actual substantive issues here?

We cannot proceed until you get some fundamentals down. Clancie and you have both claimed that only my approach rejected the null hypothesis. You are both quite wrong.

Do you understand that we have two different approaches to the problem, both of which have refuted the null hypothesis?

[BillHoyt]

Originally posted by BNiles


Does this mean that neither you nor Kerberos were doing the "experimental method"? And if you and Kerberos are doing the same "null hupothesis", why two different answers?
Kerberos = 0168
BillHoyt = .03
This seems like a big diffence to me. Could it be your counting method?
:confused:

The data sets are different.

The analytical approach is different.

The hypothesis is the same. The null hypothesis is the same.

Are we going to need two Newfs here?

[BNiles]

Originally posted by BillHoyt


The data sets are different.

The analytical approach is different.

The hypothesis is the same. The null hypothesis is the same.

Are we going to need two Newfs here?

What's a Newf? :D

[BillHoyt]

Originally posted by BNiles


What's a Newf? :D

A dog. A Newfoundland, used for water rescue. Thanz is drowning. I was hoping you weren't joining him in that activity.

Cheers,

[BNiles]

Now that makes sense..:)

I understand what is trying to be done here with J guesses exceeding the norm; however, I'm not proficient with the tools and applications to resolve the answers. I've been trying hard to follow the logic and reasoning, but I can only trust what all of you state as answers.

I feel that no matter what method or approach one uses, it is most critical that the data being considered is correct. And no disrespect, but I would have to agree with Thanz's counting method.

Don't get me wrong; I'd love for all of this to prove JE is cold reading. We could put this to bed and move on; however, when JE says, "I'm getting a J, like Joe or John." That is 1 guess. Period. Not 3. He's guessing "J" and clarifying "Joe or John".

If you said to me that you were holding an object, then asked me to guess what it was. If I said, "It's a fruit....like an apple or banana." My guess is "Fruit" not "Apple" or "Banana".

[Lurker]

Originally posted by BNiles
Now that makes sense..:)

I feel that no matter what method or approach one uses, it is most critical that the data being considered is correct. And no disrespect, but I would have to agree with Thanz's counting method.


Count me in agreement too. As long as the non "J" letters are being counted by the same method Thanz's approach is what I believed had been done in the first place. That it was not is disappointing as I think his count more accurately defines the boundary conditions of the problem.

I think Bill sacrificed accuracy in striving to be objective.

Lurker

[BillHoyt]

Originally posted by BNiles
Now that makes sense..:)

I understand what is trying to be done here with J guesses exceeding the norm; however, I'm not proficient with the tools and applications to resolve the answers. I've been trying hard to follow the logic and reasoning, but I can only trust what all of you state as answers.

I feel that no matter what method or approach one uses, it is most critical that the data being considered is correct. And no disrespect, but I would have to agree with Thanz's counting method.

Don't get me wrong; I'd love for all of this to prove JE is cold reading. We could put this to bed and move on; however, when JE says, "I'm getting a J, like Joe or John." That is 1 guess. Period. Not 3. He's guessing "J" and clarifying "Joe or John".

If you said to me that you were holding an object, then asked me to guess what it was. If I said, "It's a fruit....like an apple or banana." My guess is "Fruit" not "Apple" or "Banana".

Is he guessing "a person?" That is not at all clear. Ginger was a dog. Is he guessing "a first name"? That is not at all clear. He spat out "an Sh name". He got back an Sh last name and accepted that. That was a whole family! He accepted that answer! Is he guessing just one? No, we simply know that he stops at one hit. And we know that, at least on one occasion, he says one letter to identify two people.

So, what is it? One person? One dog? A whole family? In each case, JE accepted the sitter's answer as if that was his intended target.

Cheers,

[T'ai Chi]

Originally posted by Clancie
, and did Bill ever answer T'ai Chi's question about tallying other letters, too?


No, he didn't.

Bill simply thinks that it is appropriate to only analyze one high frequency letter, J, instead of the other high frequency letters.

He fails to realize that, say, J could be significant, while the rest of the high frequency letters could be non significant, or a mix of significant and non significant.

Therefore, his analysis is inappropriate and misleading, and a better one, that addresses all the high frequency letters at once, is needed.

[BillHoyt]

Originally posted by T'ai Chi


No, he didn't.

Bill simply thinks that it is appropriate to only analyze one high frequency letter, J, instead of the other high frequency letters.

He fails to realize that, say, J could be significant, while the rest of the high frequency letters could be non significant, or a mix of significant and non significant.

Therefore, his analysis is inappropriate and misleading, and a better one, that addresses all the high frequency letters at once, is needed.
T'ai,

We have no idea what JE knows about letter frequencies and what he doesn't. We have no need nor any reason to assume he knows the second, third, and fourth most frequent letters in the census data. The simplest assumption is that he has learned, over time, rules of thumb about names. That, for instance, "J" is the most popular first initial.

[Thanz]

Originally posted by BillHoyt
Do you understand that we have two different approaches to the problem, both of which have refuted the null hypothesis?
BillHoyt -

WTF is your point? It does not matter that kerberos also concluded that JE was cold reading. It makes no difference whatsoever.

Anyway, if you want to get down to the nitty-gritty, you have characterized Kerberos work as "suggestive". Further, you accepted that the control data used was not representative:

That means the control population is skewed a bit to UK names and isn't truly representative of US populations. To improve the analysis, we'd need to substitute a good US names list.

So, Kerberos test is out of whack for having the wrong control data. Your test is out of whack due to your poor counting methodology.

But all of this is irrelevant to the point I was making, and have been making for some time.

I'll make it again, on the hopes that you may eventually address it:On the test of the null hypothesis proposed by you, the only data set that rejects the null hypothesis is the data set compiled by you, using your flawed methodology.
Is that clear? I have never claimed that Kerberos did not find that JE was cold reading. We don't know what his method actually was (in terms of stat tools), and we know the control data is not what he hoped for. All of that is beside the point. If you want to get into a discussion of his numbers and method, do so with him. I don't know what he did.

[Thanz]

Originally posted by BillHoyt


Is he guessing "a person?" That is not at all clear. Ginger was a dog. Is he guessing "a first name"? That is not at all clear. He spat out "an Sh name". He got back an Sh last name and accepted that. That was a whole family! He accepted that answer! Is he guessing just one? No, we simply know that he stops at one hit. And we know that, at least on one occasion, he says one letter to identify two people.

So, what is it? One person? One dog? A whole family? In each case, JE accepted the sitter's answer as if that was his intended target.

Cheers,
We are just counting guesses here bill. It makes no difference what the sitter says. We are counting guesses. Your argument here makes no sense. It doesn't matter if the sitter accepts a guess as a family name or a first name. What matters is that the guess is made. And unless he says otherwise, his guesses apply to first names, as that is what he commonly brings through.

[BillHoyt]

Originally posted by Thanz
WTF is your point? It does not matter that kerberos also concluded that JE was cold reading. It makes no difference whatsoever.
Sure it does.
Anyway, if you want to get down to the nitty-gritty, you have characterized Kerberos work as "suggestive". Further, you accepted that the control data used was not representative:
This has no relevance to the question of whether or not the kerberos analysis refuted the null hypothesis. It did.

I'll make it again, on the hopes that you may eventually address it:On the test of the null hypothesis proposed by you, the only data set that rejects the null hypothesis is the data set compiled by you, using your flawed methodology.
Is that clear? I have never claimed that Kerberos did not find that JE was cold reading. We don't know what his method actually was (in terms of stat tools), and we know the control data is not what he hoped for. All of that is beside the point. If you want to get into a discussion of his numbers and method, do so with him. I don't know what he did.
It is clear. It is also clearly wrong. Kerberos also rejected the null hypothesis. With different data. With a different methodology.

We have two different approaches here that have rejected the null hypothesis.

[BillHoyt]

Originally posted by Thanz

We are just counting guesses here bill. It makes no difference what the sitter says. We are counting guesses. Your argument here makes no sense. It doesn't matter if the sitter accepts a guess as a family name or a first name. What matters is that the guess is made. And unless he says otherwise, his guesses apply to first names, as that is what he commonly brings through.

I didn't say the sitter's answer mattered. JE's acceptance of the sitter's various answers clearly indicates that your contentions are in error. That is what matters. JE does not limit himself to one guess = one person. Sometimes he says person, but it refers to a dog. Sometimes he says one initial, and clearly says he means one person. Other times he says one initial and implicitly accepted an entire family in response.

These problems matter greatly to the counting process. You keep wanting to sweep them under the rug here, but you have not offered a solution to these problems. The solution I have proffered takes most of these problems into account.

[Thanz]

Originally posted by BillHoyt

We have two different approaches here that have rejected the null hypothesis.
Even if you want to expand your null hypothesis now to be as broad as "cold reading", which it wasn't before, it still does not matter.

Both tests used flawed data and therefore the results cannot be trusted. Kerberos test used flawed control data. Your test used flawed counting data.

How many tests that have used correct counting data and the correct control data have rejected the null hypothesis? None.

Now, can we finally discuss what I have been trying to discuss? Are you ever going to stop wiggling around the issue, raising points about stuff I have not claimed, to address the simple point (which is not, as you claim "clearly wrong"):

On the test of the null hypothesis proposed by you, the only data set that rejects the null hypothesis is the data set compiled by you, using your flawed methodology.

[BillHoyt]

Originally posted by Thanz

Even if you want to expand your null hypothesis now to be as broad as "cold reading", which it wasn't before, it still does not matter.

Both tests used flawed data and therefore the results cannot be trusted. Kerberos test used flawed control data. Your test used flawed counting data.

How many tests that have used correct counting data and the correct control data have rejected the null hypothesis? None.

Now, can we finally discuss what I have been trying to discuss? Are you ever going to stop wiggling around the issue, raising points about stuff I have not claimed, to address the simple point (which is not, as you claim "clearly wrong"):

On the test of the null hypothesis proposed by you, the only data set that rejects the null hypothesis is the data set compiled by you, using your flawed methodology.

You continue to confound the hypothesis with the experimental method. Do some homework on this before you make yourself look sillier than you already do.

[Clancie]

Has any discussion thread here ever resulted in Bill admitting that he was wrong, or changing his position?

Certainly none that I recall. If anything, the more wrong he appears to be, the more deeply entrenched in his position he becomes. :rolleyes:

But...since everyone else here across the "skeptic-believer" spectrum agrees on Thanz's method, I'm going to go ahead and count the four LKL transcripts using that method and see what comes up for all the letters.

Perhaps, we can at least move the discussion forward by looking at the other letter patterns--since it is obviously futile to keep showing Bill the flaws of his method; no matter what is shown to him, it is obvious that he will not budge.

Of course, Bill is welcome to use his counting method for a tally of the rest of the letters, too.

But my prediction is that he won't, and will prefer instead to continue to argue that "J" is all that is needed.

[Thanz]

Originally posted by BillHoyt


I didn't say the sitter's answer mattered. JE's acceptance of the sitter's various answers clearly indicates that your contentions are in error. That is what matters. JE does not limit himself to one guess = one person. Sometimes he says person, but it refers to a dog. Sometimes he says one initial, and clearly says he means one person. Other times he says one initial and implicitly accepted an entire family in response.

These problems matter greatly to the counting process. You keep wanting to sweep them under the rug here, but you have not offered a solution to these problems. The solution I have proffered takes most of these problems into account.
That is BS. Your solution CREATES problems, it doesn't solve them. It doesn't matter what JE accepts as a hit, either.

Don't you remember saying this?:
We don't care about wading through the nonsense associated with JE's hit claims. He claims he is getting real information from real dead folk These dead folk should be calling out names that match the names of real folk, dead or alive. Therefore we should see a distribution of initials that match with initials fo real folk, dead or alive. Therefore, seeing JE call out too many of the most frequent initial says we must reject the null hypothesis that the names he calls correspond with the distribution of real names.

Look at again at the reading examples I posted. Is reading 1 REALLY equivalent to readings 2, 3, and 4 combined in terms of what we are trying to find out here? Aren't three separate and distinct guesses of a J connection different than 1 reading in which he says "Yes, a "J" - like John, or Joe?"

[CFLarsen]

BillHoyt, Clancie, Thanz, Lurker, whoever....

Do your own analyses and let's see what we get, OK? Time to put up or shut up. You each do your own analysis.

[Thanz]

Originally posted by BillHoyt
You continue to confound the hypothesis with the experimental method. Do some homework on this before you make yourself look sillier than you already do.
Bill, when are you actually going to address the real issues here? Lets try taking this step by step. Let's see if you can actually address them point by point.

1.Both rejections of the null hypothesis, however you feel like defining that term, were based on flawed data of one kind or another. Kerberos on flawed control data, yours on flawed counting data.

2. The test that you propose of the null hypothesis is capable of being performed with data other than the data that you yourself have compiled.

3. If we perform your test of the null hypothesis with the raw data compiled by Kerberos (his counts of intials), the null hypothesis cannot be rejected.

4. If we perform your test of the null hypothesis with the raw data that I have compiled, we also cannot reject the null hypothesis.

Do you have anything substantive at all to say about any of these points, or do you just wish to insult me again and hope that nobody realizes that you are just runninng away?

[Thanz]

Originally posted by CFLarsen
BillHoyt, Clancie, Thanz, Lurker, whoever....

Do your own analyses and let's see what we get, OK? Time to put up or shut up. You each do your own analysis.
Claus -

I have done this already!!!!

I went through the LKL transcripts and tallied the number of J guesses and the total number of guesses. It is on page 19 of this thread. I counted 43 guesses, of which 9 were J. If I plug this into the Poisson calculator, I get a probability of >= 9 of .128, which means that we cannot reject the null hypothesis.

[BillHoyt]

Originally posted by Thanz

That is BS. Your solution CREATES problems, it doesn't solve them. It doesn't matter what JE accepts as a hit, either.

Don't you remember saying this?:
You keep claiming it creates problems and you keep basing that on the unwarranted assumption that JE is making a guess for a person. The transcripts clearly call this into question. We have dogs, we have two people for one name, we have an entire family. Although JE said, in all but one case, words that made it appear he was talking a single person, he accepted responses that made it clear that that wasn't the case.

The problem becomes believing your presuppositions or looking at the data. I chose to look at the data. We are, after all, discussing JE's process. It in no way appears to have the one person/one name relationship you presume.

And let us look at my quote in context this time, eh?

Grenard:
This is why a compendium of common and rare items, for a single sitter, is often the validating scenario rather than singling out and weighing such items as oners.Won't the probabilities for a series of facts, some common, some rare, exceed chance if they are correct and fall below chance if they are not?

Hoyt:

We don't care about wading through the nonsense associated with JE's hit claims.
I was responding to Grenard's suggestion that the better approach was to analyze claimed hits. The most charitable interpretation is that you simply misunderstood. I wouldn't want to suggest you had other motives for pulling it out of context.

[BillHoyt]

Originally posted by Thanz

Bill, when are you actually going to address the real issues here? Lets try taking this step by step. Let's see if you can actually address them point by point.

1.Both rejections of the null hypothesis, however you feel like defining that term, were based on flawed data of one kind or another. Kerberos on flawed control data, yours on flawed counting data.

2. The test that you propose of the null hypothesis is capable of being performed with data other than the data that you yourself have compiled.

3. If we perform your test of the null hypothesis with the raw data compiled by Kerberos (his counts of intials), the null hypothesis cannot be rejected.

4. If we perform your test of the null hypothesis with the raw data that I have compiled, we also cannot reject the null hypothesis.

Do you have anything substantive at all to say about any of these points, or do you just wish to insult me again and hope that nobody realizes that you are just runninng away?
It is you who are running. I will discuss these when you have demonstrated competence in the fundamental concepts. Do you yet get the difference between the null hypothesis and the experimental method?

Shreiking shrilly won't help. Demonstrating an understanding will.

[Thanz]

Originally posted by BillHoyt

You keep claiming it creates problems and you keep basing that on the unwarranted assumption that JE is making a guess for a person. The transcripts clearly call this into question. We have dogs, we have two people for one name, we have an entire family. Although JE said, in all but one case, words that made it appear he was talking a single person, he accepted responses that made it clear that that wasn't the case.

The problem becomes believing your presuppositions or looking at the data. I chose to look at the data. We are, after all, discussing JE's process. It in no way appears to have the one person/one name relationship you presume.

If we have no idea what JE is making a guess for, why count at all? Doesn't that make the whole thing a crapshoot? you say that my one-person, one guess presumption is unwarranted. Where is the evidentiary backup for your assumption that "A J - jim or Joe" refers to three persons? Use your freakin head. You say I can't assume he is making a guess for one person, or even a person at all. If that is true, it is even worse to assume that he is making 3 guesses for 3 people, which you have done.

I notice you still haven't addressed my direct points. I wonder why that is?

Also - look at the rest of your quote. It describes you doing exactly what you say I can't - attributing his guesses to letter initials of people.

[Thanz]

Originally posted by BillHoyt

It is you who are running. I will discuss these when you have demonstrated competence in the fundamental concepts. Do you yet get the difference between the null hypothesis and the experimental method?

Shreiking shrilly won't help. Demonstrating an understanding will.
Dude, I don't think that you will ever address these. But let's take a shot, just to humour you. The hypothesis is what we are trying to prove or disprove. In this case, you are saying that this is cold reading. Despite the fact that your actual hypothesis, helpfully italicized, was "JE is cold-reading and his "J" guesses will show this by being significantly more frequent than chance alone would dictate. " If you want to truncate that to "JE is cold reading" now, whatever. If you then want to truncate your own null hypothesis to "JE is NOT cold reading", knock yourself out.

The experimental method is what we use to test the hypothesis. In this case, counting the J guesses, the total number of guesses, and using the Poisson distribution to determine significance. The Census data was used as a control, and we used it to calculate the expected number of J's in the sample.

Based on this experimental method, and based on your data, you rejected the null hypothesis. If we use your experimental method, but we use data that was collected properly either by Kerberos or myself, we cannot reject the null hypothesis.

Now, will you finally address my points?

[BillHoyt]

Originally posted by Thanz
If we have no idea what JE is making a guess for, why count at all? Doesn't that make the whole thing a crapshoot?
We're trying to see what process JE uses. We have to look at the evidence rather than make assumptions. Then we construct an hypothesis and an experimental method to test that hypothesis.
you say that my one-person, one guess presumption is unwarranted. Where is the evidentiary backup for your assumption that "A J - jim or Joe" refers to three persons? Use your freakin head. You say I can't assume he is making a guess for one person, or even a person at all. If that is true, it is even worse to assume that he is making 3 guesses for 3 people, which you have done.
I'm assuming nothing. I am using the transcripts as a guide. The dog case does not fit your assumption of one person/one guess. Neither does the single letter / two people case. Neither does the "Sh" / whole family case. Those are just three examples I found in perusing the transcript. Each of these clearly refutes the one person/one guess hypothesis. Your approach makes unwarranted assumptions that are demonstrably untrue. You need to modify your approach to account for these problems.

Also - look at the rest of your quote. It describes you doing exactly what you say I can't - attributing his guesses to letter initials of people.
Is English not your native language? I never said anything of the sort. My quote says nothing resembling what you claim it says. Holy bovine.

[T'ai Chi]

Ok, I like Claus' idea of us doing our analyses, and then reporting.

Let's make sure that we are all using the same set of transcripts to base our analyses on.

Can someone post the link(s) to the transcripts?

Then when we report our results, we should at the very minimum make sure to reveal how we counted letter uses, our hypotheses, the statistical model we are using and why, a measure of evidence against or for the null hypothesis (ie. p-value, etc.), and lastly a conclusion in terms of the problem.

[Loki]

Claus,

BillHoyt, Clancie, Thanz, Lurker, whoever....

Do your own analyses and let's see what we get, OK? Time to put up or shut up. You each do your own analysis.
THanks for the opportunity to put forward my findings.

Using a methodology that I call "Homeopathic Inverse-Poisson Astrology" [HIPA] I have analysed the various census and JE transcripts. The results are startling :

1. John Edward has a name starting with "J"! My personal theory here is that his parents psychically "guessed" this name prior to his birth.

2. John Edward and Sylvia Browne may not be the same person. Many people think this is an obvious conclusion, but via HIPA I believe I can establish this as 'fact'.

3. John Edward is a fake. Sorry Neofight and Clancie, but HIPA is 100% reliable in 80% of cases.

[BillHoyt]

Chirp chirp.

[T'ai Chi]

Let's make sure that we are all using the same set of transcripts to base our analyses on.

Can someone post the link(s) to the transcripts that we will all be using?

[BillHoyt]

Originally posted by T'ai Chi
Let's make sure that we are all using the same set of transcripts to base our analyses on.

Can someone post the link(s) to the transcripts that we will all be using?

It has been posted before, T'ai. It was a thread by renata. Transcript might be a good search term.

[Ed]

Originally posted by T'ai Chi
a measure of evidence against or for the null hypothesis (ie. p-value, etc.), .

You either reject it or not, you don't have evidence "for". Your degree was in what again?

[Lucianarchy]

How come Billy Hoyt dishonestly tried to shoehorn the data to meet his prejudiced beliefs? Doesn't Billy know that people are watching? Doesn't Billy know that his cheating only goes to discredit JREF skepticism?

[BillHoyt]

Originally posted by Lucianarchy
How come Billy Hoyt dishonestly tried to shoehorn the data to meet his prejudiced beliefs? Doesn't Billy know that people are watching? Doesn't Billy know that his cheating only goes to discredit JREF skepticism?

And just how would you address the many problems I raised with the data, Luci? What is your approach? What are your assumptions? Your hypothesis?

[T'ai Chi]

Originally posted by BillHoyt


It has been posted before, T'ai. It was a thread by renata. Transcript might be a good search term.

No dude, I am saying for someone to post it again, right here, right now, so without a doubt we are all using the same, exact, identical transcripts.

[T'ai Chi]

Originally posted by Ed

You either reject it or not, you don't have evidence "for". Your degree was in what again?

I was speaking loosely here, bub.

You reject or fail to reject the null hypothesis.

My question is what were your degrees in? I recall that you said "sample population" once....
(make sure to avoid the part in bold!)

[T'ai Chi]

Originally posted by Lucianarchy
Doesn't Billy know that his cheating only goes to discredit JREF skepticism?

Well, I for one don't associate Bill with JREF, and never ever will. :)

I agree with a lot of what Randi himself says, but not with much of what his followers (at least the bulletin board followers) say, or claim to say "for" the JREF.

[TLN]

Originally posted by T'ai Chi
(make sure to avoid the part in bold!)

Now, now... didn't we talk about glass houses?

[Thanz]

Originally posted by BillHoyt

We're trying to see what process JE uses. We have to look at the evidence rather than make assumptions. Then we construct an hypothesis and an experimental method to test that hypothesis.
Yes, some lovely general comments from Mr. Hoyt that don't actually get to the specific issues. Fairly typical.

The problem is that you have not considered the evidence when you constructed your counting model. It makes no logical sense whatsoever, and I notice that you haven't addressed my specific points regarding this.

I'm assuming nothing. I am using the transcripts as a guide. The dog case does not fit your assumption of one person/one guess.
I assume you are referring to the dog "Ginger". I have already stated why we do not count this guess - for one, he was not guessing a name, but rather a nickname, and for another he was not guessing an initial. He was trying to make a connection based on something other than the alphabet, and therefore does not belong in our count of guesses based on the alphabet.
Neither does the single letter / two people case.
Dude, I have already stated that if JE says he is getting two people with the same intial, we count two guesses. That is not hard, now is it?
Neither does the "Sh" / whole family case.
I am not going to search the transcript for this example, but it seems that JE threw out a "Sh" guess, which was validated by the sitter as a family name. It was not thrown out by JE as a family name. If it was, we exclude it as we are studying forenames, not surnames. If he just threw out a guess WITHOUT specifying that it was a surname, we count it. It makes no difference how or even if the sitter validates the guess. All that matters is the guesses he makes. The hypothesis is that he will guess J at a significantly higher rate than could be accounted for by the general population. For that analysis, we need to accurately count the guesses. You have not done this.
Those are just three examples I found in perusing the transcript. Each of these clearly refutes the one person/one guess hypothesis. Your approach makes unwarranted assumptions that are demonstrably untrue. You need to modify your approach to account for these problems.
I find it laughable that you post these as criticisms of my method, as they apply equally to your method - if not moreso. You counted the dog guess, and the family guess just based on the number of names tossed out - without regard to the sitters response. If that is incorrect, I am sure you will let me know.

You alos, however, count "J - like Jim or John" as 3 guesses, when it is clearly one guess. So, the way I see it, your method does nothing to solve the problems you claim are in my method, and your method also has its own unique problems which completely destroy its accuracy.

Now, I have answered all of your questions. Are you ever going to address any of mine? Do you not understand that when we use a proper data collection method, your testing procedure does not reject the null hypothesis?

[BillHoyt]

Originally posted by T'ai Chi


No dude, I am saying for someone to post it again, right here, right now, so without a doubt we are all using the same, exact, identical transcripts.

You asked for a link. I told you how to find it for yourself. Now I invite you to do so. Renata's thread on LKL JE transcripts. Fetch, whodini, fetch.

[BillHoyt]

Originally posted by Thanz
Yes, some lovely general comments from Mr. Hoyt that don't actually get to the specific issues. Fairly typical.
I'm not surprised you missed their import.

The problem is that you have not considered the evidence when you constructed your counting model. It makes no logical sense whatsoever, and I notice that you haven't addressed my specific points regarding this.
Please stop this tired strategy of yours. My comments specifically pointed out, repeatedly, what is actually in the transcript evidence. I have discussed both them and what I did with the data to account for them. You continue to make assumptions about JE's process. We are trying to first determine if there is any process to discuss at all. We cannot make your assumptions. Talk about JE hearing phonetically or seeing visually or making one name guess for one person, dead or alive, are all assumptions without foundation. The Ginger example specifically refutes the assumption of a "person". The "Sh" example, where JE names a whole freakin' family clearly refutes the one guess/ one person assumption. As does the case where JE calls out a single initial and specifically says it refers to two different people.

When doing experiments, much of the work is to shed as many unfounded assumptions as possible so that you test what you think you are testing. This is not a hand-waving, general comment, sir, it is essential to the scientific method.

I assume you are referring to the dog "Ginger". I have already stated why we do not count this guess - for one, he was not guessing a name, but rather a nickname, and for another he was not guessing an initial. He was trying to make a connection based on something other than the alphabet, and therefore does not belong in our count of guesses based on the alphabet.

JE started out with no claims about dog/ cat/person or iguana. He named three "spice nicknames", two of which are surnames recorded in the census data
Dude, I have already stated that if JE says he is getting two people with the same intial, we count two guesses. That is not hard, now is it?
I have said many times now that "easy" or "hard" are not issues. The problem is not that particular guess. The problem is what it means to your unwarranted assumption about the JE process. Here, he specifically says "two". That means the process, as JE sees it, includes this possibility. In the case of the "Sh" guess, he said nothing about how many people it applied to. The sitter said that matched the last name of part of her family. JE accepted it. So now we cannot assume JE will warn us when he means dozens or thousands of people. Your assumptions do not stand up to the evidence.

Now I want to address some more of your confusion about what is going on here. Here is what you said earler:

Nicknames - not part of our control data, therefore don't count. Treat this guess like a guess of a feather, or a calendar, or whatever.
Now in this latest post of yours you go on about the initials. Hmm. They're not in the census data either. But you include them. Then you say the nicknames should be excluded. But they are part of the census data. Which is it? What rule are you using? Do you even understand the need to apply rules and procedures consistently?

[Thanz]

Do we really need so many posts on which transcripts to use?

For crying out loud, here is the thread that Renata posted with the LKL transcripts:

http://www.randi.org/vbulletin/showthread.php?s=&threadid=24032

[Thanz]

Mr. Hoyt -

I would appreaciate it if you could edit the formatting of your most recent response before I respond.

[Thanz]

Here are some examples from the actual transcripts that show Mr. Hoyt's counting method to be in error:

EDWARD: Where does the Lewis or the Louis or the L-name?
CALLER: The L. I had a uncle that had died when I was a little kid.
As I understand Mr. Hoyt's counting, this counts as 3 L guesses. It is clearly one guess.

EDWARD: How are you doing, Carol. Carol, who around you has the SH connection?
CALLER: SH?
EDWARD: Like Sharon, Sherie.
CALLER: Sherum.
EDWARD: Sherum. What is that?
CALLER: That's my sister's last name.
EDWARD: OK, is she still here?
CALLER: Yes.
EDWARD: OK, do you know if there's somebody younger in that family whose passed?
CALLER: No.
This is, I think, the SH reading Mr. Hoyt is bringing up with me. I score this as one guess. It seems clear to me that he is fishing for one name, and a first name at that. Mr. Hoyt's method counts it as three. He claims that my method is illogical as the sitter validates a family name. I say that this does nothing to refute the guess JE makes - he is guessing one name. Mr. Hoyt would count this as three guesses. What is the logical basis for that?

EDWARD: Where's the Jane connection or Jeannie?
CALLER: Jane would be sister-in-law.
EDWARD: OK. Ask her. Because they're telling me to connect it either through either Janey or Jeannie.
Again, clearly one guess that Mr. Hoyt would count as two.
EDWARD: [snip] The other thing I want to talk about is the unique B name. Where is the B coming for you?
CALLER: A B?
EDWARD: Yes.
CALLER: I can't think of anything right now.
EDWARD: Well, directly connected to your mom's side of the family, where's the B name? Like Betty, like Beth or Bobby or the B connection again? Or Buddy? Just a short B name like Bud, Bill.
CALLER: No, nothing I'm -- no.
Possibly the most egregious example. I count ONE B guess. How many would Mr. Hoyt count? At least 6. Where is the logical basis for counting 6 B guesses here?

[Garrette]

Oh, my stars and garters.

He counts them as multiple guesses because they are multiple guesses. That's the point.

You are correct that he only wants one name in return, but he is giving more than one guess to get it.

[BillHoyt]

Originally posted by Thanz
This is, I think, the SH reading Mr. Hoyt is bringing up with me. I score this as one guess. It seems clear to me that he is fishing for one name, and a first name at that. Mr. Hoyt's method counts it as three. He claims that my method is illogical as the sitter validates a family name. I say that this does nothing to refute the guess JE makes - he is guessing one name. Mr. Hoyt would count this as three guesses. What is the logical basis for that?

Hello? Did you not read that? He fished for a first name, but got a family name! A whole family. JE accepted that. That is but one refutation your assumption of one guess/ one name.

o Have you found Pepper in the census data?
o Have you found Cinnamon?
o How about Brooklyn?
o Have you found all twenty-six initials in the census data?
o What is your logical basis for excluding names that are clearly part of the census data?
o What is your logical basis for including initials that are clearly not part of the census data?

[Thanz]

Originally posted by BillHoyt

Please stop this tired strategy of yours. My comments specifically pointed out, repeatedly, what is actually in the transcript evidence. I have discussed both them and what I did with the data to account for them. You continue to make assumptions about JE's process. We are trying to first determine if there is any process to discuss at all. We cannot make your assumptions. Talk about JE hearing phonetically or seeing visually or making one name guess for one person, dead or alive, are all assumptions without foundation. The Ginger example specifically refutes the assumption of a "person". The "Sh" example, where JE names a whole freakin' family clearly refutes the one guess/ one person assumption. As does the case where JE calls out a single initial and specifically says it refers to two different people.
You are also making assumptions, Mr. Hoyt. It is inevitable. You are assuming that everytime he utters a letter or a name he is making a separate guess. There is no basis for this assumption. Why have you not addressed my numbered readings above and what they show about counting methods?

If you actually read the transcipts, you see that there is evidentiary basis for my assumptions.

JE started out with no claims about dog/ cat/person or iguana. He named three "spice nicknames", two of which are surnames recorded in the census data
First, we are focussed on forenames, not surnames. Second, he is guessing a nickname, not a forename or a surname. Third, he is not making a guess based on letters, but rather a different connection. He is not doing the guess a common letter thing here - or guess any letter. It does not belong in a count of letter guesses.

I have said many times now that "easy" or "hard" are not issues. The problem is not that particular guess. The problem is what it means to your unwarranted assumption about the JE process. Here, he specifically says "two". That means the process, as JE sees it, includes this possibility. In the case of the "Sh" guess, he said nothing about how many people it applied to. The sitter said that matched the last name of part of her family. JE accepted it. So now we cannot assume JE will warn us when he means dozens or thousands of people. Your assumptions do not stand up to the evidence.
In the SH, the sitter only referred to her sister. Again, it doesn't matter what the sitter says. Why don't you understand this? We are counting his guesses. How many guesses did he make? ONE. If he says "two people with a J name" how many guesses is he making? TWO. Simple, logical, and backed by the evidence. Saying "Two people with J" is the same as saying "A J connection", getting a hit, and then saying "Another J connection". Two guesses.

Now in this latest post of yours you go on about the initials. Hmm. They're not in the census data either. But you include them. Then you say the nicknames should be excluded. But they are part of the census data. Which is it? What rule are you using? Do you even understand the need to apply rules and procedures consistently?
I really don't know what you are talking about here. I stand by what I said previously. There is more than one reason to exclude the dog - and none of them have to do with the sitter validating it as a dog.

Are you ever going to answer my specific questions that were posted above? You said you would if I explained the difference between hypothesis and experimental method, which I have done. So - where are the answers? Why don't you respond to those posts? They won't go away, you know.

[Thanz]

Originally posted by Garrette
Oh, my stars and garters.

He counts them as multiple guesses because they are multiple guesses. That's the point.

You are correct that he only wants one name in return, but he is giving more than one guess to get it.
But we are counting the number of time he guesses an initial letter. In the B example, he guesses "B", and then rattles off a bunch of examples. This does not change the fact that he makes one guess of B.

If you want to score each name, go ahead. But then you have to compare each name to the distribution of THAT NAME in the census data. What BillHoyt is doing is counting the B example the same as if he said "B? B,B,B,B,B?" or, B once in 6 different readings, which is incorrect. See my numbered readings above.

[Garrette]

Okay, then it's possible I'm speaking out of turn and ill-informed because once this thread got really statistical, I only skimmed it. If that's the case, then my apologies in advance.

But it seems to me that there is a flaw in the procedure if done your way. It reduces the actual number of JE guesses (as opposed to the number of "initial letter" JE guesses) without reducing the pool of hits/misses. This procedure, to my statistically ignorant mind, seems to guarantee a better success rate for JE than he actually deserves.

[BillHoyt]

Originally posted by Thanz
You are also making assumptions, Mr. Hoyt. It is inevitable. You are assuming that everytime he utters a letter or a name he is making a separate guess. There is no basis for this assumption. Why have you not addressed my numbered readings above and what they show about counting methods?
Oh, stop! I have explained that the data lead me to the conclusion that we cannot assume this 1 to 1 mapping that you assume.
If you actually read the transcipts, you see that there is evidentiary basis for my assumptions.
Cripes. Asked and answered. Please address my answers.
First, we are focussed on forenames, not surnames. Second, he is guessing a nickname, not a forename or a surname. Third, he is not making a guess based on letters, but rather a different connection. He is not doing the guess a common letter thing here - or guess any letter. It does not belong in a count of letter guesses.
Thank you for the correction. I meant "forename".
Yes, he said nickname, but he named actual forenames. What is your basis for excluding them? Then he got a dog, not a person. And the dog's actual name, not nickname, matched the criterion "spice". So, once again JE said one thing, and accepted something else entirely. You toss in specious assumptions and try to sweep both the count data and the more general process evidence under the rug.

In the SH, the sitter only referred to her sister. Again, it doesn't matter what the sitter says. Why don't you understand this? We are counting his guesses. How many guesses did he make? ONE. If he says "two people with a J name" how many guesses is he making? TWO. Simple, logical, and backed by the evidence. Saying "Two people with J" is the same as saying "A J connection", getting a hit, and then saying "Another J connection". Two guesses.
Last time, Thanz, because you are being dense here. The "Sh" case is a clear refutation of the 1-to-1 ratio you claim. "Sh" was not a forename. It was a surname. A whole freakin' family. JE accepted the answer. In doing so, he provides clear evidence that he is not guessing in the 1-to-1 process you claim.

Thanz, this debate is going nowhere because you continue to ignore what I am presenting. You continue to mischaracterize what I am saying. It is irksome.

[Skeptical Greg]

Originally posted by Thanz
quote:
--------------------------------------------------------------------------------
EDWARD: How are you doing, Carol. Carol, who around you has the SH connection?
CALLER: SH?
EDWARD: Like Sharon, Sherie.
CALLER: Sherum.
EDWARD: Sherum. What is that?
CALLER: That's my sister's last name.
EDWARD: OK, is she still here?
CALLER: Yes.
EDWARD: OK, do you know if there's somebody younger in that family whose passed?
CALLER: No.
--------------------------------------------------------------------------------


This is, I think, the SH reading Mr. Hoyt is bringing up with me. I score this as one guess. It seems clear to me that he is fishing for one name, and a first name at that. Mr. Hoyt's method counts it as three.



Garrette and Billy have responded here, but here's my .02 anyway since the ' Diogenes ' method gets a five count...

1. .... who around you has the SH connection?

2. Sharon ?

3. Sheri ?

4. ... is she still here?

5. OK, do you know if there's somebody younger in that family whose passed?



What's hillarious is that people actually pay money to be interrogated by this clown.. Why can't law enforcement agencies take advantage of this tendancy?

[Clancie]

Actually there are 5 LKL transcripts, the first two are no longer archived at LKL. There are the three renata used (01, 02, 03) plus these two from 1998:

Transcript #1 (6/98) Not available at LKL

LKL Transcript #1, June 1998 (http://www.nytix.com/TVShows/NewYork/JohnEdward/transcripts/)

Transcript #2 (10/98) Not at LKL. Greta van Susteren guest hosts

LKL Transcript #2, October 1998 (http://www.johnedward.net/lkl_1030.htm)

[Thanz]

Originally posted by BillHoyt


Hello? Did you not read that? He fished for a first name, but got a family name! A whole family. JE accepted that. That is but one refutation your assumption of one guess/ one name.
No. Once again - hits/misses make no difference. WE ARE COUNTING GUESSES. It doesn't matter what the sitter says, or what JE accepts as a hit. Do I need to give you your own monkey here?

o Have you found Pepper in the census data?
It doesn't matter. The census is not a survey of nicknames. We do not know the expected distribution of nicknames, which is what JE was guessing.
o Have you found Cinnamon?
See above.
o How about Brooklyn?
I'm not sure why I would even look. What is your point here?
o Have you found all twenty-six initials in the census data?
Are you saying that all 26 letters are not reflected in the census? The distribution of intials in the census was given by juninho on page 10 of this thread.
o What is your logical basis for excluding names that are clearly part of the census data?
What names? Once again, the census data is a survey of first names. We used it to get our expected distribution for each initial letter of first names. It is not a survey of nicknames. Nicknames are not the same as first names. We do not know the expected distribution of nicknames. Therefore, we do not count them. If you are counting the number of dead crows in a field, and you come across a dead sparrow, do you count it too because it is a dead bird?
o What is your logical basis for including initials that are clearly not part of the census data?
I have no idea what you are talking about here.

[BillHoyt]

Originally posted by Thanz

No. Once again - hits/misses make no difference. WE ARE COUNTING GUESSES. It doesn't matter what the sitter says, or what JE accepts as a hit. Do I need to give you your own monkey here?

Alright. I'm done with you. Come back around thanksgiving, when I'm more tolerant of turkeys.

[Thanz]

Originally posted by BillHoyt


Alright. I'm done with you. Come back around thanksgiving, when I'm more tolerant of turkeys.
Just run away. That's fine. Without, I note, addressing any of my specific points about your results and the rejection of the null hypothesis, despite saying you would.

Perhaps we could take this in baby steps.

WHY do you think it is relevant to consider what the sitter says?

How did you score the SH reading? On what basis?

[Lurker]

What the sitter responds with is TOTALLY irrelevant. IF JE were to preface his statement with something like "I am getting a nickname here..." or something similar then it might be more important. But he does not.

Since we know by JE's own words that he focuses on first names we can presume that when he makes a guess, without any statement before the guess, that the guess is for a first name. That is JE's intent. On the rare occasion where the sitter confirms as a nickname, or as a dog, unless there was prior modification of intent by JE, we should assume each guess is for a first name.

Lurker

[Clancie]

Bill,

Are you planning to join in on counting for all 5 transcripts to see if your "J'" pattern remains consistent (as well as to check on the other high frequency letter patterns, in case "J" was just an anomaly?)

[Thanz]

Originally posted by Garrette
But it seems to me that there is a flaw in the procedure if done your way. It reduces the actual number of JE guesses (as opposed to the number of "initial letter" JE guesses) without reducing the pool of hits/misses. This procedure, to my statistically ignorant mind, seems to guarantee a better success rate for JE than he actually deserves.
For the analysis that we are doing, we are not interested in whether any of the guesses are hits or misses.

The basic idea here is that if JE is cold reading, he will focus on the more frequent initials as they are more likely to get a hit. So, the theory goes, if he is a cold reader he will make a lot of "J" guesses (for example) as "J" is the most common letter for names to begin with.

Of course, if he were real he would make more J guesses than other letters for the same reason - it is the most common. So, we compare how many J guesses he makes to how many we would expect based on the census to see if he makes statistically significantly more J guesses.

In order to do the count, we need to count the total number of guesses for each initial letter. For our purposes, we have been considering a guess of "John" to be equivalent to a guess of "J". I have some reservations about this, but that is how the count was done.

The current disagreement is about what to count as one "guess". I count as one guess any connection he tries to make that is for one person with the same letter - in B example above, he is trying to make one B connection, with a number of specific guesses. Mr. Hoyt counts each name guess as if it were a separate guess.

Another example is the Jane/Jeannie guess. One guess, with two names to increase chance of a hit. Mr. Hoyt counts it as two, as if JE had said "a J connection" once in two separate readings. I count it as one, which would be the same as if he just said "a J connection" in this reading. Note that "J connection" would actually have been a wider net (better for cold reading) than "Jane/jeannie" is. Mr. Hoyt inaccurately counts these as two, even though it is a narrower guess than even one of "J connection".

I hope this summary helps you understand what we are going on about.

[voidx]

Posted by Thanz:
Another example is the Jane/Jeannie guess. One guess, with two names to increase chance of a hit. Mr. Hoyt counts it as two, as if JE had said "a J connection" once in two separate readings. I count it as one, which would be the same as if he just said "a J connection" in this reading. Note that "J connection" would actually have been a wider net (better for cold reading) than "Jane/jeannie" is. Mr. Hoyt inaccurately counts these as two, even though it is a narrower guess than even one of "J connection".
While I know that you guys are trying to do a statistical analysis of first letter name guess' I feel in this stated case above you're starting to mix first letter guess' with actual name guess'. Something I think is wrong. If he is making a guess by stating a starting letter then fine I agree with you. But if he states Jane/Jeannie, that is two "name" guess'. While I agree it would be a narrower range for accuracy than just a "J connection" in actual practice it doesn't really matter. JE tosses out names all the time, in almost every reading, and is often wrong. No one ever bats an eye at the numerous name toss outs that do not fit, but rather those that do when they happen. So again while I agree he's being more specific I don't give him credit for this because no one ever takes him to task if he's not even close, its still a safe bet for him because he can always invoke the "difficulty" of telepathic communication excuse.

edited to add: However, I suppose from a mindset of a first letter guess Jane/Jeannie would just be 1 guess, as they both start with J. But I don't know that its logical to start lumping "name" guess' in with first "letter" guess'

[Thanz]

Originally posted by voidx

edited to add: However, I suppose from a mindset of a first letter guess Jane/Jeannie would just be 1 guess, as they both start with J. But I don't know that its logical to start lumping "name" guess' in with first "letter" guess'
I think that we are in agreement. Earlier in the thread when I suggested that a guess of a name should be treated differently than a guess of just a letter, Mr. Hoyt said it was "Malarky". I disagree with him, but I still did a count with his rule of just looking at the first initial.

If we were counting name guesses (and charting those specific name guesses - ie, counting how many "John" guesses, etc) then I would agree that you need to count each name guess separately. As we are just counting letters however, we shouldn't be counting extra guesses.

I think that what we generally see is that JE will either guess a letter, a letter with a couple of specifics, or just a couple of specifics. In most cases, the initial within the guess is consistent. On other occasions, he guesses somewhat phonetically (Ellen/Helen, J or G, C or K). In those cases, I counted one for each letter.

[neofight]

Originally posted by Thanz

But we are counting the number of time he guesses an initial letter. In the B example, he guesses "B", and then rattles off a bunch of examples. This does not change the fact that he makes one guess of B.

If you want to score each name, go ahead. But then you have to compare each name to the distribution of THAT NAME in the census data. What BillHoyt is doing is counting the B example the same as if he said "B? B,B,B,B,B?" or, B once in 6 different readings, which is incorrect. See my numbered readings above.

Thanz, I don't understand how a logical person can reasonably look at this in any other way. JE never gets the initial wrong. For instance, he will never say I'm getting a short name like Fel, Bill, or Rob. Now, to count those examples as three separate names, an "F", a "B" and an "R" name would make sense. Something like "Steve, Stephanie or Stan", would not. That should only be considered as one "S" name. Anything else would skew the count in such a way as to render it misleading, and therefore useless.

If two skeptics cannot agree on something as basic as this, I don't see how there's any hope for coming up with a fair way to count these names......neo

[Darat]

Originally posted by neofight

...snip...

JE never gets the initial wrong.

...snip...

Neo - are you saying that JE never gives a letter or a name sound out and gets no takers/connection?

[neofight]

Originally posted by Darat


Neo - are you saying that JE never gives a letter or a name sound out and gets no takers/connection?

No, Darat, that is not what I am saying, although I would have to add that it is fairly rare that the sitter cannot identify either the letter or name that JE gives them.

But to further clarify my point, no, what I am saying is that John does not mix his letters when he is conveying to the sitter the name that he is getting, except in the unique cases that we've already discussed. i.e. in the soft "G" and "J" instance, the hard "C" and "K" instance, or the case where there is a prominent "L" sound, but softened by a vowel, as in "Elena" or "Ellen" or even "Helen". John admittedly does sometimes have a problem differentiating these sorts of names when he hears them. Since he "hears" these names clairaudiently, phonetics obviously would be a factor here.......neo

[voidx]

Posted by neofight:
John admittedly does sometimes have a problem differentiating these sorts of names when he hears them. Since he "hears" these names clairaudiently, phonetics obviously would be a factor here
This is also complete hearsay. We only have John's word to verify this phonetic difficulty. It has not been clarified what he "hears" period. Is it in his own voice? Does he hear it in the spirits voice? Do they have accents? Does he "hear" different languages? If he does do they get translated into english, or some other language he understands? If so are the translated voices his? Or the spirits? All these above questions would go towards understanding what possible phonetic problems JE might experience with his clairaudience. Do we have a detailed description of how and what he hears that covers all our bases here? I don't think you can state anything "obviously" when it comes to the as of yet non proven ability of clairaudience, sorry.

[BillHoyt]

Originally posted by neofight


No, Darat, that is not what I am saying, although I would have to add that it is fairly rare that the sitter cannot identify either the letter or name that JE gives them.

But to further clarify my point, no, what I am saying is that John does not mix his letters when he is conveying to the sitter the name that he is getting, except in the unique cases that we've already discussed. i.e. in the soft "G" and "J" instance, the hard "C" and "K" instance, or the case where there is a prominent "L" sound, but softened by a vowel, as in "Elena" or "Ellen" or even "Helen". John admittedly does sometimes have a problem differentiating these sorts of names when he hears them. Since he "hears" these names clairaudiently, phonetics obviously would be a factor here.......neo

"Somebody has a name like would be off of a map or something. Like they would be named for a location. Like they called the person, you know, New York or they called the person, Brooklyn or they called the person, you know, Boston."

"Somebody has a nickname after a spice, like pepper? Who's got a spice name?... Salty or pepper, cinnamon."

Explain these, please. Phonetically How does one "hear" a map name? How does one "hear" a spice name?

[voidx]

Posted by neofight:
Something like "Steve, Stephanie or Stan", would not. That should only be considered as one "S" name. Anything else would skew the count in such a way as to render it misleading, and therefore useless.
Also to clarify this example would be considered one S "letter" under Thanz' explanation. If we were counting names they would certainly be 3 seperate guess', and not phonetically very similiar either. And yes I know it was just an example, but lets not get confused. To count this as 1 S "name" would skew just as badly as counting it as 3 S "first letters". How about this for a suggestion. Would it be possible to count "letter" guess' seperately from "name" guess'? The problem here is that he often uses both within the same reading. He often starts with a letter connection and then moves on to some narrowing techniques with specific names starting with that letter. I just think if you count them and analyze them seperately, that would eliminate the problem of how they should be counted if you only use one category for all.

[BillHoyt]

Originally posted by voidx

This is also complete hearsay. We only have John's word to verify this phonetic difficulty. It has not been clarified what he "hears" period. Is it in his own voice? Does he hear it in the spirits voice? Do they have accents? Does he "hear" different languages? If he does do they get translated into english, or some other language he understands? If so are the translated voices his? Or the spirits? All these above questions would go towards understanding what possible phonetic problems JE might experience with his clairaudience. Do we have a detailed description of how and what he hears that covers all our bases here? I don't think you can state anything "obviously" when it comes to the as of yet non proven ability of clairaudience, sorry.

One of the problems here is the transcripts make a complete mockery of these claims. Certain parties here therefore ignore the transcripts.

Wait... something's coming through. It sounds like a spice name. Tamarind? Basil? Oregano? Something that sounds like that.

ROTFLMAO!

[Clancie]

Posted by BillHoyt

Explain these, please. Phonetically How does one "hear" a map name? How does one "hear" a spice name?
For starters, Bill, JE doesn't say he hears a spice name.

Next...you do understand how he says he gets the information, right? That not all of it comes to him clairaudiently. The spice name is very consistent with that part of the process, Bill.

[BillHoyt]

Chervil?

[voidx]

Posted by BillHoyt:
Explain these, please. Phonetically How does one "hear" a map name? How does one "hear" a spice name?
Heheh ahhhh he wouldn't "hear" this one. He'd "see" or "feel" it. The magically 3 step catch all that is clairaudience/voyance/sentience covers all my friend :D. Consistency be damned.

[BillHoyt]

Originally posted by Clancie

For starters, Bill, JE doesn't say he hears a spice name.

Next...you do understand how he says he gets the information, right? That not all of it comes to him clairaudiently. The spice name is very consistent with that part of the process, Bill. [/B]

Are you reading or doing your nails? Pay attention, you might learn something. Here is what was just said by neoblight:

"admittedly does sometimes have a problem differentiating these sorts of names when he hears them. Since he "hears" these names clairaudiently, phonetics obviously would be a factor here"

This was neoblight's claim, Clownie.

[BillHoyt]

Originally posted by voidx

Heheh ahhhh he wouldn't "hear" this one. He'd "see" or "feel" it. The magically 3 step catch all that is clairaudience/voyance/sentience covers all my friend :D. Consistency be damned.

Isn't it a riot? These woos haven't a clue.

No, no, it isn't Chervil. Much longer sounding, but like Chervil. Ohh, its "Chinese Five Spice?"

My mother cooks with Chinese Five Spice!

Bravo! Isn't that amazing folks. Larry King Live will be right back, after JE takes the potato out of his ears...

[voidx]

"Somebody has a name like would be off of a map or something. Like they would be named for a location. Like they called the person, you know, New York or they called the person, Brooklyn or they called the person, you know, Boston."
The other problem with this one is that it is anything but consistent. He "see's" things in his own frame of reference, so if its bloody New York, then why isn't it clear? And ok Brooklyn is close to New York in meaning so perhaps we can give him getting confused there....but Boston? How can people not admit he's fishing for information here, how is Boston similiar to New York and Brooklyn....ahhhh yes, perhaps there's a connection in his own frame of reference, utter convinience.

Posted by BillHoyt:
Are you reading or doing your nails? Pay attention, you might learn something. Here is what was just said by neoblight:

"admittedly does sometimes have a problem differentiating these sorts of names when he hears them. Since he "hears" these names clairaudiently, phonetics obviously would be a factor here"

This was neoblight's claim, Clownie.
I see where you might be getting confused here Bill. Different mediums, as the explanation goes, have differring strengths with each of the three clair abilitilies, being audience/voyance/sentience or hear/see/feel. So sometimes they hear letters, or names, sometimes they visualize them, or sometimes they are used within his own frame of reference, like a memory of a girl he knew named John/Jane/Joey :D. These three abilities can be interchanged at will, and hence my statement above, when something doesn't make sense at all like you're above example any of the three abilities can be claimed responsible, whether or not that is the medium in questions strongest of the three or not. Neofight was making reference to how he "hears" when he in fact does "hear". You get a whole other explanation for how he "see's" and "feels". So to be clear Neo is not making the claim that JE only "hears".

[Thanz]

Ah, Mr. Hoyt. You are here and reading this thread.

We obviously have a fundamental disagreement on counting. I need to understand why you think we should take the sitters responses into account when counting JE's guesses. Why does it matter? Instead of just yelling at me that I don't understand your points, perhaps you could explain it.

[Clancie]

Bill,

You're doing great with the insults. How's the count of all transcripts and the high frequency letters going? :rolleyes:

There's no indication he was getting the spice name phonetically. He often receives pictures and symbols, even with names, rather than having everything spelled out (as you seem to assume it is).

[BillHoyt]

Originally posted by Thanz
Ah, Mr. Hoyt. You are here and reading this thread.

We obviously have a fundamental disagreement on counting. I need to understand why you think we should take the sitters responses into account when counting JE's guesses. Why does it matter? Instead of just yelling at me that I don't understand your points, perhaps you could explain it.

Who said the sitter's responses are being taken into account? Is English not your native language? Re-read my posts about this, and quit wasting my time.

[BillHoyt]

Originally posted by Clancie
Bill,

You're doing great with the insults. How's the count of all transcripts and the high frequency letters going? :rolleyes:

There's no indication he was getting the spice name phonetically. He often receives pictures and symbols, even with names, rather than having everything spelled out (as you seem to assume it is).

Goody. Another nitwit thesis. What "symbol" could he have seen that covers the map name example? How about the picture of "salty"? Or "pepper" Or "cinnamon?" Explain these in detail.

[voidx]

Posted by Thanz:
I need to understand why you think we should take the sitters responses into account when counting JE's guesses.
The only time this would matter is if the sitter gave some sort of clue without giving JE the whole name, and then he made another, refined guess at a name. But then this would be counted anyway. That and we have no way of seeing visual clues that might lead JE to refine a name or first letter guess. But still, it wouldn't matter that much, you could still count all the guess'.

Posted by BillHoyt:
Who said the sitter's responses are being taken into account?
So it's agreed, sitter responses do not affect the count of guess' and shouldn't be taken into account. Let's move on, next point of contention?

[Thanz]

Originally posted by BillHoyt
Who said the sitter's responses are being taken into account? Is English not your native language? Re-read my posts about this, and quit wasting my time.
Where does the idea that "Sh" is a family name come from? It comes from the sitter. How is that not taking the sitter's response into account? In order for JE to have accepted it, he had to get the feedback. I am saying that neither the feedback nor the acceptance of JE are relevant. Why do you tihnk they are? Or at least, why do you think JE's acceptance of a hit is relevant?

If she had said nothing, would you have counted it? If she had said "NO" would you have counted it? Did you count it at all (as a family name or otherwise)? On what basis?

I will answer my own questions in advance - I count it as one "S" guess, regardless of what the sitter says or doesn't say, or how JE counts it as a 'hit'. It was not qualified upfront by JE as a family name, therefore we must count it. If he had qualified it as a family name, I would not include it at all - as we are studying forenames, not surnames.

[Thanz]

Here is a snippet from one of the readings. I am interested to know how people score it for guesses.
EDWARD: Where is -- sorry -- where does the K-name like Karen come up?
CALLER: I don't know. EDWARD: Yes, you do. There is a C or a K connection directly to you or to this family, from what they are telling me. So it either means it's who they are -- put your sister on hold and think about your family. There is some type of C or K connection and they're also telling me to tell you 11, which either means that the 11th month November or the 11th of a month has some type of significance. And why are they showing me...

[BillHoyt]

Anybody got an animated smiley with a bird flying WAY over head?

[Thanz]

Originally posted by BillHoyt
Anybody got an animated smiley with a bird flying WAY over head?
Did the bird crap on you when he went over your head?

Are you even able to answer a direct question? You have been avoiding them all over the place.

You said that you would address my points once I explained the difference between hypothesis and experimental method. I have done this. You still avoid simple direct questions. Is it because you know that you are incorrect, but not mature enough to admit a mistake?

[BillHoyt]

Originally posted by Thanz

Did the bird crap on you when he went over your head?

Are you even able to answer a direct question? You have been avoiding them all over the place.

You said that you would address my points once I explained the difference between hypothesis and experimental method. I have done this. You still avoid simple direct questions. Is it because you know that you are incorrect, but not mature enough to admit a mistake?

Thanz,

I have answered everything. You continue to fail to understand the answers. It is useless to continue with you because you twist my answers into your answers or no answers at all.

I have said before the sitters responses don't matter for the counting. I have repeated it. I have said before that JE's acceptance of those responses also does not matter for the counting. I have repeated that. I have also clearly said that JE's acceptance of certain responses matters greatly to your 1 guess - 1 person assumption. It refutes it.

[Lurker]

Originally posted by BillHoyt


Goody. Another nitwit thesis. What "symbol" could he have seen that covers the map name example? How about the picture of "salty"? Or "pepper" Or "cinnamon?" Explain these in detail.

Well, in "Blues Clues" there are characters; Mr. Pepper, Mrs. Salt and they have two children, Cinnamon and Paprika. Maybe John Edward is getting these characters in his visions? Is John Edward a big fan of "Blues Clues"?

Lurker

[voidx]

Originally posted by Thanz
Here is a snippet from one of the readings. I am interested to know how people score it for guesses.
EDWARD: Where is -- sorry -- where does the K-name like Karen come up?
CALLER: I don't know. EDWARD: Yes, you do. There is a C or a K connection directly to you or to this family, from what they are telling me. So it either means it's who they are -- put your sister on hold and think about your family. There is some type of C or K connection and they're also telling me to tell you 11, which either means that the 11th month November or the 11th of a month has some type of significance. And why are they showing me...


I would score it like this.

1 K letter guess
1 Karen name guess
1 C letter guess
1 11 number guess
1 narrowing guess of the 11th month novemeber
1 narrowing guess of the 11th day of any month
1 obvious mark for fishing for information :D