The "Process" of John Edward

[BillHoyt]

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]

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]

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]

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. )

 

[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]

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. )

Yes, your crow example is wrong. Dreadfully wrong.

Lurker

 

[BillHoyt]

Yes, your crow example is wrong. Dreadfully wrong.

Lurker

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

 

[T'ai Chi]

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]

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. )

Cheers,

 

[Thanz]

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]

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]

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]

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]

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]

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. )

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]

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

 

[BillHoyt]

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

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