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ATTN: George Duncan

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thompnickson2

ATTN: George Duncan

All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:

Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea

** RIP, Rheem Jarrett

Nicholas Thompson

Emeritus Professor of Ethology and Psychology

Clark University

[hidden email]

https://wordpress.clarku.edu/nthompson/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

George Duncan-2

Re: ATTN: George Duncan

Hey, Nick, glad to see you continuing to address these basic statistical questions. I'll respond from a Bayesian perspective, which I think is mostly compatible with Pierce's writings though I haven't read much at all of his.

First, most all Bayesians and indeed perhaps a majority of statisticians would consider the posed question, "Is it true that the coin I hold in my hand is a fair coin?", can have no physical meaning as no such coin has "real-world" existence, certainly no one could construct such a coin.

Second, to me and other Bayesians (and perhaps Pierce) a more meaningful question goes something like this:

I entertain that the coin I hold has a certain probability p of being flipped heads. Prior to ever flipping the coin I have a probability distribution over possible values of p. This is based on everything I know about the coin (who gave it to me, what it looks like, my past experience in flipping other coins, etc.) This probability distribution may well be personal to me. A common way of characterizing such distributions on p is through one of the family of beta distribution, a family chosen because it is plausible for cases where the coin looks ordinary and there is nothing strange in how I came by the coin. The nice thing mathematically is that after flipping the coin, say seven times and getting 2 heads and 5 tails, the posterior distribution, which now reflects your uncertainty given this experience, is again a beta distribution with just different parameters. Beautiful! If I have time tomorrow I'll show you how this works.

Third, there are hints of frequency theory (so non-Bayesian) perspective in what you write, most likely reflective of those statistics courses you took way back when--60 years ago!. As I said, the Bayesian perspective is I believe more compatible with Pierce. Long ago statisticians like Pearson and R.A. Fisher were not Bayesians. Statisticians today are much more likely to be Bayesians. The reason for this is mainly twofold, (1) the wide range of applications in areas like engineering, economics and medicine that are amenable to Bayesian analysis, and (2) the enormous increase in computational power that makes implementation of Bayesian analysis possible (few problems are as easy as the coin toss, and what if the prior distibution is not in beta form?).

George Duncan

Emeritus Professor of Statistics, Carnegie Mellon University
georgeduncanart.com

See posts on Facebook, Twitter, and Instagram

Land: (505) 983-6895

Mobile: (505) 469-4671

My art theme: Dynamic exposition of the tension between matrix order and luminous chaos.

"Attempt what is not certain. Certainty may or may not come later. It may then be a valuable delusion."

From "Notes to myself on beginning a painting" by Richard Diebenkorn.

"It's that knife-edge of uncertainty where we come alive to our truest power." Joanna Macy.

On Sun, May 24, 2020 at 12:56 PM <[hidden email]> wrote:

All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

Eric Charles-2

Re: ATTN: George Duncan

In reply to this post by thompnickson2

Nick,

I feel like this fast-forwarded some how. The first and most important thing Perice wants is for us to think clearly about our concepts, right?

So, before we get going into this, the first thing we need to do is figure out whether we agree on the following:

The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern.

That is, while we can hypothesize about whether the coin is fair based on all sorts of things - studying how it was made, measuring it's symmetry, etc. - we recognize that any such evidence would be irrelevant in the face of results from a very large number of flips.

Phrased the other way around: The claim that a given coin is "fair", if we are thinking clearly, a claim about what result we will see if we flip the coin a very large number of times. Nothing more, nothing less. Though we expect the construction of a coin to impact whether or not it is "fair", we are definitely not asserting that it has any particular construction when we assert that it is fair.**

** Note the connection with our prior discussion of psychological terms and human insides.

-----------

Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist

American University - Adjunct Instructor

[hidden email]

On Sun, May 24, 2020 at 2:56 PM <[hidden email]> wrote:

All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

Frank Wimberly-2

Re: ATTN: George Duncan

"The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern."

George will correct me and I defer to his greater knowledge of probability theory. I believe a fair coin the distribution of heads/tosses will have an expected value of 1/2. For a large number of tosses the probability of an equal number of heads and tails is vanishingly small.

Frank

On Sun, May 24, 2020 at 8:25 PM Eric Charles <[hidden email]> wrote:

Nick,
I feel like this fast-forwarded some how. The first and most important thing Perice wants is for us to think clearly about our concepts, right?

So, before we get going into this, the first thing we need to do is figure out whether we agree on the following:

The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern.

That is, while we can hypothesize about whether the coin is fair based on all sorts of things - studying how it was made, measuring it's symmetry, etc. - we recognize that any such evidence would be irrelevant in the face of results from a very large number of flips.

Phrased the other way around: The claim that a given coin is "fair", if we are thinking clearly, a claim about what result we will see if we flip the coin a very large number of times. Nothing more, nothing less. Though we expect the construction of a coin to impact whether or not it is "fair", we are definitely not asserting that it has any particular construction when we assert that it is fair.**

** Note the connection with our prior discussion of psychological terms and human insides.

-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor
[hidden email]

On Sun, May 24, 2020 at 2:56 PM <[hidden email]> wrote:
All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

Frank Wimberly
140 Calle Ojo Feliz
Santa Fe, NM 87505
505 670-9918

George Duncan-2

Re: ATTN: George Duncan

You are correct, Frank.

On Sun, May 24, 2020 at 8:36 PM Frank Wimberly <[hidden email]> wrote:

"The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern."

George will correct me and I defer to his greater knowledge of probability theory. I believe a fair coin the distribution of heads/tosses will have an expected value of 1/2. For a large number of tosses the probability of an equal number of heads and tails is vanishingly small.

Frank

On Sun, May 24, 2020 at 8:25 PM Eric Charles <[hidden email]> wrote:
Nick,
I feel like this fast-forwarded some how. The first and most important thing Perice wants is for us to think clearly about our concepts, right?

So, before we get going into this, the first thing we need to do is figure out whether we agree on the following:

The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern.

That is, while we can hypothesize about whether the coin is fair based on all sorts of things - studying how it was made, measuring it's symmetry, etc. - we recognize that any such evidence would be irrelevant in the face of results from a very large number of flips.

Phrased the other way around: The claim that a given coin is "fair", if we are thinking clearly, a claim about what result we will see if we flip the coin a very large number of times. Nothing more, nothing less. Though we expect the construction of a coin to impact whether or not it is "fair", we are definitely not asserting that it has any particular construction when we assert that it is fair.**

** Note the connection with our prior discussion of psychological terms and human insides.

-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor
[hidden email]

On Sun, May 24, 2020 at 2:56 PM <[hidden email]> wrote:
All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

--
Frank Wimberly
140 Calle Ojo Feliz
Santa Fe, NM 87505
505 670-9918
-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

George Duncan

Emeritus Professor of Statistics, Carnegie Mellon University
georgeduncanart.com

See posts on Facebook, Twitter, and Instagram

Land: (505) 983-6895

Mobile: (505) 469-4671

My art theme: Dynamic exposition of the tension between matrix order and luminous chaos.

"Attempt what is not certain. Certainty may or may not come later. It may then be a valuable delusion."

From "Notes to myself on beginning a painting" by Richard Diebenkorn.

"It's that knife-edge of uncertainty where we come alive to our truest power." Joanna Macy.

Eric Charles-2

Re: ATTN: George Duncan

In reply to this post by Frank Wimberly-2

Frank,

Indeed!

And yet, that is what the concept entails... isn't it?

When we wonder about whether or not a coin is "fair", we wonder if it will produce an equal number of heads and tails with no pattern if we kept on flipping it forever. We will need to bring statistics into the discussion because, as you point out, the odds of getting exactly 1/2 on any given run is small, and because short runs could easily appear to have a pattern.

What we need to avoid is mistaking the concepts wrapped up in the statistics for the concept we are actually interested in. If we are interested in "fair", we are not directly wondering about the statistical probabilities associated with any given run, but rather we are using the statistics to aid in our inferences regarding the broader concept.

Thus statistics will always feed the inference, never replace it. If we tested a fair coin long enough, we would eventually expect to get a run of 100 heads. That means that if we tested enough fair coins, one of them would eventually give 100 heads on the first 100 flips. As such, even seeing something as unlikely as 100 heads in a row does not definitively rule out that a coin is fair; we would still be inferring regarding the (un)fairness.

See also the classic Dilbert comic, attached

-----------

Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist

American University - Adjunct Instructor

[hidden email]

On Sun, May 24, 2020 at 10:36 PM Frank Wimberly <[hidden email]> wrote:

"The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern."

George will correct me and I defer to his greater knowledge of probability theory. I believe a fair coin the distribution of heads/tosses will have an expected value of 1/2. For a large number of tosses the probability of an equal number of heads and tails is vanishingly small.

Frank

On Sun, May 24, 2020 at 8:25 PM Eric Charles <[hidden email]> wrote:
Nick,
I feel like this fast-forwarded some how. The first and most important thing Perice wants is for us to think clearly about our concepts, right?

So, before we get going into this, the first thing we need to do is figure out whether we agree on the following:

The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern.

That is, while we can hypothesize about whether the coin is fair based on all sorts of things - studying how it was made, measuring it's symmetry, etc. - we recognize that any such evidence would be irrelevant in the face of results from a very large number of flips.

Phrased the other way around: The claim that a given coin is "fair", if we are thinking clearly, a claim about what result we will see if we flip the coin a very large number of times. Nothing more, nothing less. Though we expect the construction of a coin to impact whether or not it is "fair", we are definitely not asserting that it has any particular construction when we assert that it is fair.**

** Note the connection with our prior discussion of psychological terms and human insides.

-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor
[hidden email]

On Sun, May 24, 2020 at 2:56 PM <[hidden email]> wrote:
All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

--
Frank Wimberly
140 Calle Ojo Feliz
Santa Fe, NM 87505
505 670-9918
-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
FRIAM-COMIC http://friam-comic.blogspot.com/

Frank Wimberly-2

Re: ATTN: George Duncan

Funny. True but probably irrelevant.

That's a joke.

---
Frank C. Wimberly
140 Calle Ojo Feliz,
Santa Fe, NM 87505

505 670-9918
Santa Fe, NM

On Tue, May 26, 2020, 7:53 AM Eric Charles <[hidden email]> wrote:

Frank,
Indeed!

And yet, that is what the concept entails... isn't it?

When we wonder about whether or not a coin is "fair", we wonder if it will produce an equal number of heads and tails with no pattern if we kept on flipping it forever. We will need to bring statistics into the discussion because, as you point out, the odds of getting exactly 1/2 on any given run is small, and because short runs could easily appear to have a pattern.

What we need to avoid is mistaking the concepts wrapped up in the statistics for the concept we are actually interested in. If we are interested in "fair", we are not directly wondering about the statistical probabilities associated with any given run, but rather we are using the statistics to aid in our inferences regarding the broader concept.

Thus statistics will always feed the inference, never replace it. If we tested a fair coin long enough, we would eventually expect to get a run of 100 heads. That means that if we tested enough fair coins, one of them would eventually give 100 heads on the first 100 flips. As such, even seeing something as unlikely as 100 heads in a row does not definitively rule out that a coin is fair; we would still be inferring regarding the (un)fairness.

See also the classic Dilbert comic, attached

.

-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor
[hidden email]

On Sun, May 24, 2020 at 10:36 PM Frank Wimberly <[hidden email]> wrote:
"The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern."

George will correct me and I defer to his greater knowledge of probability theory. I believe a fair coin the distribution of heads/tosses will have an expected value of 1/2. For a large number of tosses the probability of an equal number of heads and tails is vanishingly small.

Frank

On Sun, May 24, 2020 at 8:25 PM Eric Charles <[hidden email]> wrote:
Nick,
I feel like this fast-forwarded some how. The first and most important thing Perice wants is for us to think clearly about our concepts, right?

So, before we get going into this, the first thing we need to do is figure out whether we agree on the following:

The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern.

That is, while we can hypothesize about whether the coin is fair based on all sorts of things - studying how it was made, measuring it's symmetry, etc. - we recognize that any such evidence would be irrelevant in the face of results from a very large number of flips.

Phrased the other way around: The claim that a given coin is "fair", if we are thinking clearly, a claim about what result we will see if we flip the coin a very large number of times. Nothing more, nothing less. Though we expect the construction of a coin to impact whether or not it is "fair", we are definitely not asserting that it has any particular construction when we assert that it is fair.**

** Note the connection with our prior discussion of psychological terms and human insides.

-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor
[hidden email]

On Sun, May 24, 2020 at 2:56 PM <[hidden email]> wrote:
All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

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140 Calle Ojo Feliz
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505 670-9918
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thompnickson2

Re: ATTN: George Duncan

In reply to this post by Eric Charles-2

Eric inter alia,

Isn’t that a joke about the presidential campaign of our current housing and urban development secretary, Ben Carson?

If ever there were a mantra of Pragmatism it would be: You can never be sure!

Nick

Nicholas Thompson

Emeritus Professor of Ethology and Psychology

Clark University

[hidden email]

https://wordpress.clarku.edu/nthompson/

From: Friam <[hidden email]> On Behalf Of Eric Charles
Sent: Tuesday, May 26, 2020 7:53 AM
To: The Friday Morning Applied Complexity Coffee Group <[hidden email]>
Subject: Re: [FRIAM] ATTN: George Duncan

Frank,

Indeed!

And yet, that is what the concept entails... isn't it?

When we wonder about whether or not a coin is "fair", we wonder if it will produce an equal number of heads and tails with no pattern if we kept on flipping it forever. We will need to bring statistics into the discussion because, as you point out, the odds of getting exactly 1/2 on any given run is small, and because short runs could easily appear to have a pattern.

See also the classic Dilbert comic, attached

-----------

Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist

American University - Adjunct Instructor

On Sun, May 24, 2020 at 10:36 PM Frank Wimberly <[hidden email]> wrote:

"The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern."

George will correct me and I defer to his greater knowledge of probability theory. I believe a fair coin the distribution of heads/tosses will have an expected value of 1/2. For a large number of tosses the probability of an equal number of heads and tails is vanishingly small.

Frank

On Sun, May 24, 2020 at 8:25 PM Eric Charles <[hidden email]> wrote:
Nick,
I feel like this fast-forwarded some how. The first and most important thing Perice wants is for us to think clearly about our concepts, right?

So, before we get going into this, the first thing we need to do is figure out whether we agree on the following:

The concept "fair", entails, in its entirety, that the coin will, in the long run, produce an equal number of heads and tails with no pattern.

That is, while we can hypothesize about whether the coin is fair based on all sorts of things - studying how it was made, measuring it's symmetry, etc. - we recognize that any such evidence would be irrelevant in the face of results from a very large number of flips.

Phrased the other way around: The claim that a given coin is "fair", if we are thinking clearly, a claim about what result we will see if we flip the coin a very large number of times. Nothing more, nothing less. Though we expect the construction of a coin to impact whether or not it is "fair", we are definitely not asserting that it has any particular construction when we assert that it is fair.**

** Note the connection with our prior discussion of psychological terms and human insides.

-----------
Eric P. Charles, Ph.D.
Department of Justice - Personnel Psychologist
American University - Adjunct Instructor

On Sun, May 24, 2020 at 2:56 PM <[hidden email]> wrote:
All, particularly, George—

In an earlier larding, I argued that Peirce’s idea of truth is essentially a statistical one. So:

Is it true that the coin I hold in my hand is a fair coin?

Let the coin be flipped once, and it comes out heads, what do you think? No way of telling, right? OK. Flip it again. Heads again. Two heads in a row. P=0.25. Sure, I guess so. It could be fair. Flip it again. Hmmm. Three heads in a row………Five heads in a row. P= 03125. You know? I think that coin is probably not fair. “Fair” in this formulation means the infinite distribution of H and T coinflips is .5. “Probably not” means, the chances that this coin’s flips are drawn from a .5 distribution is less than 0.0312 and my threshold of dis belief is 0.05. Thus, when I say that the coin is not fair, that inference is in part a statement about me, and the truth of the matter, the limit of the distribution of flips, is prospective. But the notion that there can be some truths of some matters is absolutely essential to science. Why else would we flip the coin?

Now George: why am I bothering you about this. Three questions:
Is this valid statistical logic? I ask because all psychologists are only amateur statisticians, and many of us bugger up the logic. In particular, we are known to confuse type I and type II error.
Is this Peirce’s logic? If not, what is Peirce’s logic; and
Is Peirce’s logic the ORIGIN of the logic of statistical inference that I was taught 60 years ago in graduate school**. If so, which among the famous statisticians, Pearson, Spearman, Fischer, etc., read Peirce?

[signed]

TLOLTT*

* The Little Old Lady Tasting Tea
** RIP, Rheem Jarrett

Nicholas Thompson
Emeritus Professor of Ethology and Psychology
Clark University
[hidden email]
https://wordpress.clarku.edu/nthompson/

-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
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Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
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--
Frank Wimberly
140 Calle Ojo Feliz
Santa Fe, NM 87505
505 670-9918
-- --- .-. . .-.. --- -.-. -.- ... -..-. .- .-. . -..-. - .... . -..-. . ... ... . -. - .. .- .-.. -..-. .-- --- .-. -.- . .-. ...
FRIAM Applied Complexity Group listserv
Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam
un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com
archives: http://friam.471366.n2.nabble.com/
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