Everyone who makes a personal pledge, such as a gift in a will, is invited to join the Carlyle Circle, and is invited to special events, receptions and lectures.

之後，深深懷念20年前的David，他提議弄 The Deming Circle.

Thank you for preparing this piece of David's story for us. The Funeral service will be on Monday 20th May at Kings College Chapel, Aberdeen University. Anyone who is able to attend is welcome.

If we could have your story of how you knew David and the input he had on your life before then, we would be grateful.

Thank You

Deborah Armstrong

**Remembering Prof. David Kerridge**

By Hanching
Chung

Ever since I wrote to Prof. David Kerridge and
received a long reply to my questions in 1995, I think David was my mentor. Although we did meet, I knew we are friends. Let me take advantage of this note to offer our sincere condolences of
Taiwanese Deming Circle
to his family.

Indeed, I am one of members of David’s
worldwide Deming Philosophy Circle.
David put the idea of it to some friends in email, but I laughed at the idea of
it, cited many historical cases failed.Nevertheless, David continued to be my
never-ending resource on Deming/Shewhart philosophy. Nearly every year,
David and his daughter Sarah got some well-thought papers. In his late years,
he even shared with us his papers in his Apple computer disk.

David Wrote Dr. Deming’s obituary in

*European Quality*( "The official journal of the European Organization for Quality"), Circa 1995. He involved in Dr. Deming’s seminars since late 1980s. In Wikipedia’s “W. Edwards Deming” item, a note tells us that

"Of the four experts, Deming, who can be the harshest as a teacher, seems the most humanistic, insisting that it is every person's right to have "joy in work." He used to say "pride" until David Kerridge, a professor at the University of Aberdeen, pointed out that the Book of Ecclesiastes says "joy" in two different verses. Deming, whose one known hobby is writing liturgical masses, switched to joy. He estimates that no more than two in a hundred managers and ten in a hundred workers now have joy in their work. InQuality or else: the revolution in world businessLloyd Dobyns, Clare Crawford-Mason – 1991.

I joined British Deming Association (BDA)
several years since 1996. In each issue
of the

*Variations*newsletter, I enjoyed David and Sarah’s short essays very much, for example, “Guilty by Association” tells a typical Dr. Deming’s reaction to so-called Total Quality Management (TQM). Their English are good and I hoped someday to publish bilingual version of their collection of essays. Unfortunate, this idea was only partially completed yet. David was the chairman of BDA’s Research Committee. His annual reports for the committee were models of any research organization.
Thanks to David’s kind permissions, In 1998
I put two essays in my Chinese web site〝Transformation not Tampering〞 and “A Model of Transformation” which I thought it is very
inspiring. But David was learning all the time, when I proposed to put it in
the coming book edited by me about 2008, David thought it is not very good and
suggested some other article. In 1999 Feb. I put their essay “Operational
Meaning” translation in my website. (Deming Electronic Network website used to
have a collection of David & Sarah Kerridge’s essays at that time.)

David
and Sarah’s contributions to some professional journals are worth mentioned. For
example, “ Applying the DEMING PHILOSOPHY to the Safety System “ ,

*Professional Safety*; Aug 2006, Vol. 51 Issue 8, p.52. Their contributions to*The**Journal for Quality & Participation*are very good: Dr. Deming's cure for a sick system (;Dec 96, Vol. 19 Issue 7, p.24) and “Managing complexity” (March 1, 1997).
I read
“Managing complexity” in

*The Quality Yearbook*(*Cortada and Woods (editors) , McGraw-Hill , 1998) and wrote to David to congratulate them. A Chinese version of it was put in our book**System and Variations*(2010 ). David also wrote a foreword for our book*The Essential Deming*(2009). David also helped me to translate Dr. Deming’s paper On Probability As a Basis For Action (*American Statistician*, 29, 1975, pp.146-52).
David was an authority on Walter Shewhart’s
philosophy. He helped the paper

“W. Edwards Deming’s mentor and others who
made a significant impact on his views during the 1920s and 1930s” (Beth
Blankenship and Peter B. Petersen,

even the handwriting, easy to read. Yes, the main tribute is from ASQC.”

*Journal of Management History*, Vol. 5 Iss: 8, pp.454 – 467). I remember how happy he was when I discovered a "*Tribute*" for Dr. Shewhart in U.S.A..His reply to my mail listed for your reference: “Thanks for this web site. I have extracted the photographs from the html pages, and enlarged them. This makes all the writing in the pictures,even the handwriting, easy to read. Yes, the main tribute is from ASQC.”

He was also pleased to know that Dr. Deming’s
name was mentioned in the note of one of Sir Ronald
Aylmer, Fisher (1890-1962) paper in Fisher’s Archieve. I knew
his profound knowledge of statistical thinking so I asked him many “Big
Questions”. One of his answer is “I think that R A Fisher saw further than
Neyman and Pearson, but not as far as Shewhart.” In 2011,
I had several mails with him about the

*Scientific Inference*by Sir Harold Jeffreys. He was always very helpful.
In 2009 David had a sense of urgency and replied
to one of my mails to him:

“I am afraid that the generation of us who knew and worked with Dr Deming is getting older. We badly need a new generation of scientists who understand the Shewhart/Deming ideas and will take them forward. So much research remains to be done...”

May 13, 2013, Taipei, Taiwan

******Reference

1995年 鍾漢清加入英國戴明協會（BDA）。認識 David Kerridge 教授，深受關愛。獲創始會長 Henry R. Neave 博士贈其佳作 The Deming Dimension

12月與中華民國品質管制學會合辦第一屆「戴明紀念研討會」，蒙當時任飛利普副總裁的許祿寶先生幫忙。我印象最深的是他說：「企業管理界成名的多為理論家和顧問，我們這些實踐者尚未獲應有的肯定。」有道理。

1998?

Prof.
David Kerridge贈論文『The Theory of Knowledge』等

; 前英國戴明協會的「統計研究小組」（仍續由 Dave Kerridge領導），在著名的醫學刊物上登一 Shewhart管制圖的應用：六個英國醫院和醫師的績效（包括去年震驚全世界的醫師兼凶手的高死亡 率），利用二項式 Shewhart管制圖來區分共同因誤為特殊因，來學習科學的改善。文章資料如下： Mohammed MA, Cheng KK, Rouse A, Marshall T."Bristol, Shipman and clinical governance:
Shewhart's forgotten lessons." Lancet 2001;357:463-67. (to be published on
the internet 9th of Feb http://www.thelancet.com/
and on the 10th in paper form)Lancet 手術中用的柳葉刀或稱刺血針，常用它來代表醫學這一專業，例如 The Lancet為創始於1823年的英文醫學、醫物刊物，現在為周刊。中國青島有「柳葉刀叢書」。

Dear Hanching,

Thanks for your thoughts. I especially appreciate your pointing out Professor's Johnson excellent speech, containing similar themes, which I found at:

http://deming.ces.clemson.edu/pub/den/deming_johnson1.htm

Dear Hanching,

Thanks for your thoughts. I especially appreciate your pointing out Professor's Johnson excellent speech, containing similar themes, which I found at:

http://deming.ces.clemson.edu/

2006

HC/
David Hsu 2006-10-27 08:35:15

朋友的刊物{逍遙}（每月/期360元）已出5期，我是後知者。

在「明目」與兩位留德的老師談德國政治和文化。周四買四本書，兩本與英國文化相關，讀趙珩{彀外譚屑──近五十年聞見摭憶}(北京：三聯書店) 中之數篇，還有些古風範，也讀到很間接的"朋友"…….

中華民國品質學會QKC每月聚會(地點： 台北市羅斯福路二段75號九樓)。我與林公孚老師談昨天之學習：包括"時空 spread"…..

十月10/26主講人陳善德 題目為 教育品質：「系統思考」與「心」教育【會前讀David KERRIDGE教授寫 Deming and Learning……..】

主持人陳寬仁老師剛從台中的「英雄館—勤益」回來：請吃太陽餅。他最近"驛馬星動"，剛從廈門歸又要……「去北京要交文章一篇 前言 結語 請看看 不必客氣 請修正 ：民生建設過程中『貨惡其棄於地也』之體認」

我 草草回復：但憑記憶：中山先生著作(含三民主義)似乎著重infrastructures基礎建設，所以有蔣中正先生之{民生育樂補篇}。我認為過去50 年台灣剛好建立民生產業多樣產品之世界級能力，而這正是大陸最短缺的，也是將中山思想提到滿足全世界要求之水平。所以大陸之改革開放，其實是這領域的迎頭 趕上。而台灣貢獻頗大，這當然包括台灣掌握民生產品的品質與生產力訣竅，這，或許加上大陸的改革可開創第二春。大陸Juran 的quality handbook 一印即10萬本或可當作一明證。

朋友的刊物{逍遙}（每月/期360元）已出5期，我是後知者。

在「明目」與兩位留德的老師談德國政治和文化。周四買四本書，兩本與英國文化相關，讀趙珩{彀外譚屑──近五十年聞見摭憶}(北京：三聯書店) 中之數篇，還有些古風範，也讀到很間接的"朋友"…….

中華民國品質學會QKC每月聚會(地點： 台北市羅斯福路二段75號九樓)。我與林公孚老師談昨天之學習：包括"時空 spread"…..

十月10/26主講人陳善德 題目為 教育品質：「系統思考」與「心」教育【會前讀David KERRIDGE教授寫 Deming and Learning……..】

主持人陳寬仁老師剛從台中的「英雄館—勤益」回來：請吃太陽餅。他最近"驛馬星動"，剛從廈門歸又要……「去北京要交文章一篇 前言 結語 請看看 不必客氣 請修正 ：民生建設過程中『貨惡其棄於地也』之體認」

我 草草回復：但憑記憶：中山先生著作(含三民主義)似乎著重infrastructures基礎建設，所以有蔣中正先生之{民生育樂補篇}。我認為過去50 年台灣剛好建立民生產業多樣產品之世界級能力，而這正是大陸最短缺的，也是將中山思想提到滿足全世界要求之水平。所以大陸之改革開放，其實是這領域的迎頭 趕上。而台灣貢獻頗大，這當然包括台灣掌握民生產品的品質與生產力訣竅，這，或許加上大陸的改革可開創第二春。大陸Juran 的quality handbook 一印即10萬本或可當作一明證。

2009

Dear Hanching,

>We encountered an issue in the Essential Deming proof-reading. Perhaps

you

>can help .

>We don't know how to type statistical symbols.

>Perhaps you can forward them to us.

>

>First, the formula of Shewhart's optimal sample size (which Tippett

Yes, I am afraid that mathematical and statistical symbols are a

terrible nuisance. They were designed in the days of pencil and paper,

so they could be anything you like. But they don't fit in with modern

conditions.

Unfortunately I don't have the Shewhart paper you are referring to, so I

don't know what formula you want. The other problem is that I work on an

Apple computer (made in Taiwan), and know nothing about how to type the

symbols on a Microsoft based machine. There is, unfortunately not

complete standardisation of type-faces.

Anyway, if you show me what formula you want, I can try to set it up on

my machine, and send you the result.

Henry Neave told me recently that he had problems of the same kind, in

producing a new edition of his statistical tables. But he found all the

answers by searching various articles on the internet. He also has an

Apple machine.

>Second help , if you can forwards "Probability as Basis of Action"

(textform not PDF form.

the formatting, but unfortunately the tables get messed up.

Dear Hanching,

I have just checked back over my correspondence with henry Neave. He

used the "Equation Editor" that comes free with Appleworks (but not with

the more advanced iWork package that I use now.

If you have much of this sort of thing to do, I believe that MathMagic,

which is much more powerful than the free Equation Editor has versions

for all operating systems.

But as I said, if you let me know what equation you want, I will see if

I can set it up.

Best wishes

Dear Hanching,

>I can not open the file. I checked with my draft, only symbol of

>"Hypothesis" needed. Other placed in my book seems solved.

plain text.

In Deming's ideal world of cooperation between competitors, there would

be none of this deliberate incompatibility. But that seems a long way

off.

Best wishes

DavidForeword

戴明文選:從統計品管到淵博知識系統

(The Essential
Deming)

複 雜之管理 （David & Sarah Kerridge）

系統與變異: 淵博知識與理想設計法 (2010)

David Kerridge 教授的兩封信都貼在台

11/20

Dear Hanching,

>

>Actually I am thinking about the "complexity" paper.

Yes, that's probably the most suitable one. The others assume knowledge

of Shewhart and Deming concepts, which is (sadly) rare even among Deming

enthusiasts.

>By the way, I just suggest the sponsor to use our educational

ministry's

>resourse to invite you to join the conference. Is it possible for you

to

>visit Taiwan next year?

I am afraid I have had to give up all travel in recent years. Its a

great pity, as I was thinking, before you wrote, how interested I would

be in such a conference.

Anyway, thank you for the kind thought. I hope the conference is a great

success.

>It seems quite difficult to get members of Deming Philosophy Circle

>together.

I am afraid that the generation of us who knew and worked with Dr Deming

is getting older. We badly need a new generation of scientists who

understand the Shewhart/Deming ideas and will take them forward.

So much research remains to be done.

2010

>I wonder the "Tribute" (bottom picture) was by ASQC?

>

>http://www.statisticool.com/shewhart.htm

Thanks for this web site. I have extracted the photographs from the html

pages, and enlarged them. This makes all the wrinting in the pictures,

even the handwriting, easy to read.

Yes, the main tribute is from ASQC.

8/20/2010

>The book mentioned about George Barnard and yesterday I knew he died in

> 2002 and first time saw his portrait.

Yes, I knew George Barnard. He was our external examiner for statistics

when I was at Sheffield University, and I often saw him at meetings in

London.

>In 2008 I read a draft d a paper by Deming with a reference to Fisher's

>Statistical Inference book but later Deming decide to drop it for

unknown

>reason. (I knew many statisticians prefer Fisher not to write the

book,)

Fisher was a remarkable man, but nobody could argue with him. I expect

Deming did not want to give the impression that he approved of Fisher's

theory of inference. Fisher recognised the weakness of inference based

on repeated sampling from the same population - something that is rarely

possible in practice, and equally rarely relevant to the problems of

science. But Fisher's solution was to refer to sampling from a

"hypothetical infinite population." This idea seems too indefinite for

science, since it is not subject to operational definition. But only

Shewhart saw his way through this.

I think that the problem was that Fisher began as a mathematician, and

then became a scientist. That's the wrong way round. Deming and Shewhart

were scientists who became statisticians.

For many mathematicians their abstract models are more real than the

real world itself.

>Yesterday I suggested David Hsu here to write System of Profound

Knowledge

>for Beginners, He asked me advice for his two years book project here,

At a research meeting in New York, Deming sid to me:

"We are all beginners here."

**灣戴明圈****Dear Hanching Chung**11/20

Dear Hanching,

>

>Actually I am thinking about the "complexity" paper.

of Shewhart and Deming concepts, which is (sadly) rare even among Deming

enthusiasts.

>By the way, I just suggest the sponsor to use our educational

ministry's

>resourse to invite you to join the conference. Is it possible for you

to

>visit Taiwan next year?

great pity, as I was thinking, before you wrote, how interested I would

be in such a conference.

Anyway, thank you for the kind thought. I hope the conference is a great

success.

**11/20/09****>Thanks for the information.**>It seems quite difficult to get members of Deming Philosophy Circle

>together.

I am afraid that the generation of us who knew and worked with Dr Deming

is getting older. We badly need a new generation of scientists who

understand the Shewhart/Deming ideas and will take them forward.

So much research remains to be done.

2010

>I wonder the "Tribute" (bottom picture) was by ASQC?

>

>http://www.statisticool.com/

Thanks for this web site. I have extracted the photographs from the html

pages, and enlarged them. This makes all the wrinting in the pictures,

even the handwriting, easy to read.

Yes, the main tribute is from ASQC.

8/20/2010

**Dear Hanching Chung**>The book mentioned about George Barnard and yesterday I knew he died in

> 2002 and first time saw his portrait.

when I was at Sheffield University, and I often saw him at meetings in

London.

>In 2008 I read a draft d a paper by Deming with a reference to Fisher's

>Statistical Inference book but later Deming decide to drop it for

unknown

>reason. (I knew many statisticians prefer Fisher not to write the

book,)

Deming did not want to give the impression that he approved of Fisher's

theory of inference. Fisher recognised the weakness of inference based

on repeated sampling from the same population - something that is rarely

possible in practice, and equally rarely relevant to the problems of

science. But Fisher's solution was to refer to sampling from a

"hypothetical infinite population." This idea seems too indefinite for

science, since it is not subject to operational definition. But only

Shewhart saw his way through this.

I think that the problem was that Fisher began as a mathematician, and

then became a scientist. That's the wrong way round. Deming and Shewhart

were scientists who became statisticians.

For many mathematicians their abstract models are more real than the

real world itself.

>Yesterday I suggested David Hsu here to write System of Profound

Knowledge

>for Beginners, He asked me advice for his two years book project here,

"We are all beginners here."

**8/27/2010**

**Dear Hanching Chung**

>If it not a bothering for you, how about help me understand " Fisher vs

>Shewhart" their relationship to the concept of analytic study.

>Or my question is wrongly put. Sorry, I try to pick up some of my

>understanding of your commentary,

answer properly. It is to do with the whole nature of scientific method,

on which even the philosophers are confused.

I think that R A Fisher saw further than Neyman and Pearson, but not as

far as Shewhart.

Anyway, I will try to put some thoughts in writing, but will not hurry

it, as this is a difficult one to explain.

Best wishes

**Dear David,**

Thanks. I think it is worthwhile to write down what you
think and later expand it into an more professional article to share
with more more people,

Then I am glad to be a catalyst for learning.

I spent all last two weeks to correct or rewrite
this year;s book on System Thinking and Variations, It runs to about 500
pages (my part is about 300 pages, You & Sarah's one rewrite more
than four times,) I realised next one shout set limit to no more than
300 pages altogether.

Today I went to National University to read two revised books by George Box One is 1978's

*Statistics for Experimenters*and the other is*You can nearly improve everything*around 2005 while the first edition in*Box on Quality and Discovery (2000)*. He come Shewhart-Deming Cycle with his model in an article wrote in 1999.
Best Regards,

2011

昨天接受英國
KERRIDGE 教授的信。我兩周前向他提「科學推論」的大哉問，可能讓他忙翻了。現在畢業了，真好！因為我以前(1978年)在導師課(一對一)考老師的問題，他們都在學為考卷上回敬我。

### 請教David Kerridge 關於 ' epistemological probability".

Scientific Inference (Harold Jeffreys) 科學推斷

Dear

Dear

*David,*
5/26/11

# Scientific Inference by Sir Harold Jeffreys

Dear

I came across a Chinese translation of

I can browse it in Google Books, it is a third edition.

I don't know exactly the meaning of his ' epistemological probability".

And what is the main difference between his view of probability and dr. Deming's.

Perhaps you might be of help to explain it to us.

Regards,

Hanching

*David,*I came across a Chinese translation of

*Scientific Inference*by Sir Harold Jeffreys. Unfortunately it is a second edition one .I can browse it in Google Books, it is a third edition.

I don't know exactly the meaning of his ' epistemological probability".

And what is the main difference between his view of probability and dr. Deming's.

Perhaps you might be of help to explain it to us.

Regards,

Hanching

5/2

Dear
Hanching,

That's a really difficult question. I will do what I can, but I had

better think first how to put it.

It happens that I spent years trying to solve to problems of "What is

probability?"

Scientific Inference was one of the books that I found very inspiring.

But so were a lot of others.

Anyway, I will try to make some useful comments next week. But I must

find a way to reduce it to a few words.

That's a really difficult question. I will do what I can, but I had

better think first how to put it.

It happens that I spent years trying to solve to problems of "What is

probability?"

Scientific Inference was one of the books that I found very inspiring.

But so were a lot of others.

Anyway, I will try to make some useful comments next week. But I must

find a way to reduce it to a few words.

6/8/11

Dear
Hanching

Just to let you know that I am still working on answering your question.

I am including in the comparison the commonly taught frequency view of

probability as well, because I can't see how to compare Jeffreys and

Deming without it.

I don't have a copy of Scientific Inference, though I read it many

times. But I do have copy of Jeffreys other book "The Theory of

Probability" and I attach a copy of the preface, which is relevant.

Best wishes

Just to let you know that I am still working on answering your question.

I am including in the comparison the commonly taught frequency view of

probability as well, because I can't see how to compare Jeffreys and

Deming without it.

I don't have a copy of Scientific Inference, though I read it many

times. But I do have copy of Jeffreys other book "The Theory of

Probability" and I attach a copy of the preface, which is relevant.

Best wishes

6/8/11

Dear
David,

Thanks.

Actually we can read most parts of the

Thanks again.

Thanks.

Actually we can read most parts of the

*Scientific Inference*- Harold Jeffreys (The Google Books)Thanks again.

Dear
Hanching,

Thanks for the reference to Scientific Inference on Google books. My

out-of date system won't let me access it at present, but I will note

the address.

However, I thought you were asking about probability, rather than

inference. Perhaps I misunderstood the question.

Anyway, I will do my best, and then you can ask further questions.

Thanks for the reference to Scientific Inference on Google books. My

out-of date system won't let me access it at present, but I will note

the address.

However, I thought you were asking about probability, rather than

inference. Perhaps I misunderstood the question.

Anyway, I will do my best, and then you can ask further questions.

8/9/11

Dear
Hanching

I am sorry to have been such a very long time in answering your

interesting question. There have been two reasons. I have been ill, and

found it hard to concentrate. But that would not have stopped me if the

question did not require a lot of concentration.

Both Dr Deming and Sir Harold Jeffreys held views of probability that

are different from those usually taught. They are, in fact extreme

cases. Sir Harold Jeffreys held views that are regarded by most people

as very out-of-date, being the same as those held by LaPlace a hundred

years before.

Deming (following Shewhart) based his views on the new philosophy of

science that came in with Relativity and Quantum Theory. This is so

advanced that few other statisticians are even aware of it yet. Shewhart

assuned that it would be universally adopted in time: but there is

little sign of it yet. (John W Tukey is the one exception that comes to

mind)

That's *why* there is a difference, and why both differ from the views

of probability in most textbooks. But to explain what the difference is,

is not easy, without explaining the different philosophical viewpoints.

That's what I have spent a lot of time trying to do. It makes it no

easier that Deming did not explain his view of probability explicitly. I

had to deduce it from remarks he made in research meetings, and in

papers like "On Probability as a Basis for Action."

Note that for Jeffreys, and those before him, probability is simply a

matter of logic: action may result from probability, but the nature of

probability is not defined in terms of action. For Shewhart and Deming,

everything scientific is defined in terms of action, rather than

thought, because actions can be observed, while thoughts can not.

This really requires a book to explain it - a pity Shewhart didn't write

one on this topic. But he probably felt that the problem of defining

probability was still not completely solved.

I spent years on this problem using the same advanced philosophical

viewpoint as Shewhart, long before I met Deming. I couldn't find any

other statistician in the UK who understood what I was saying. And I

heard Deming discussing his ideas with others, who couldn't see what he

meant. So he had the same problem.

This may be enough to be going on with. The rest may take a long time to

express in simple words. I intend to try, but it can't be hurried.

Best wishes

I am sorry to have been such a very long time in answering your

interesting question. There have been two reasons. I have been ill, and

found it hard to concentrate. But that would not have stopped me if the

question did not require a lot of concentration.

Both Dr Deming and Sir Harold Jeffreys held views of probability that

are different from those usually taught. They are, in fact extreme

cases. Sir Harold Jeffreys held views that are regarded by most people

as very out-of-date, being the same as those held by LaPlace a hundred

years before.

Deming (following Shewhart) based his views on the new philosophy of

science that came in with Relativity and Quantum Theory. This is so

advanced that few other statisticians are even aware of it yet. Shewhart

assuned that it would be universally adopted in time: but there is

little sign of it yet. (John W Tukey is the one exception that comes to

mind)

That's *why* there is a difference, and why both differ from the views

of probability in most textbooks. But to explain what the difference is,

is not easy, without explaining the different philosophical viewpoints.

That's what I have spent a lot of time trying to do. It makes it no

easier that Deming did not explain his view of probability explicitly. I

had to deduce it from remarks he made in research meetings, and in

papers like "On Probability as a Basis for Action."

Note that for Jeffreys, and those before him, probability is simply a

matter of logic: action may result from probability, but the nature of

probability is not defined in terms of action. For Shewhart and Deming,

everything scientific is defined in terms of action, rather than

thought, because actions can be observed, while thoughts can not.

This really requires a book to explain it - a pity Shewhart didn't write

one on this topic. But he probably felt that the problem of defining

probability was still not completely solved.

I spent years on this problem using the same advanced philosophical

viewpoint as Shewhart, long before I met Deming. I couldn't find any

other statistician in the UK who understood what I was saying. And I

heard Deming discussing his ideas with others, who couldn't see what he

meant. So he had the same problem.

This may be enough to be going on with. The rest may take a long time to

express in simple words. I intend to try, but it can't be hurried.

Best wishes

Dear David,

Thanks very much. I am very surprised. I thought you gave up to popularize the subject.

I like to keep you inform that Joyce is editing a book of Dr. Deming's papers and speeches. The book will publish by McGraw-Hill Next year.

Last week I read a book review from

The article was listed for your reference. Thanks again.

Best Wishes,

Thanks very much. I am very surprised. I thought you gave up to popularize the subject.

I like to keep you inform that Joyce is editing a book of Dr. Deming's papers and speeches. The book will publish by McGraw-Hill Next year.

Last week I read a book review from

*New York Times*. I wrote a note in the blog that you told me about 10 years ago that while Dr. Deming was in England, he helped to redistribute the papers by Mr Bayes.The article was listed for your reference. Thanks again.

Best Wishes,

# The Mathematics of Changing Your Mind

###### By JOHN ALLEN PAULOS

8/9/11

Dear
Hanching,

Thanks for the information about Joyce Orsini's forthcoming book, and

the review of the book on Bayes Theorem.

I think that there is a lot more to be discovered about Bayes Theorem.

It is certainly a very important practical tool. For example, my email

is scanned for spam by a programme based on Bayes Theorem. But I rather

suspect it is not being used correctly - and still works.

In 1964 I was a Research Fellow, and two of us were investigating

methods of medical diagnosis. In other words, trying to develop

statistical rules for guessing what illness a patient is suffering from,

based on a limited number of tests or symptoms.

We found a paper, written by a computer scientist, that claimed to use

Bayes Theorem in medical diagnosis. But his method did not allow for the

obvious fact that different symptoms are not statistically independent.

We were shocked at such ignorance, and misuse of statistical theory. So

we set out to compare all the best methods we could find, including new

ones we developed ourselves, based on multivariate logistic analysis,

and another based on comparing each case with all the data in a

database.

Sad to say, the "wrong" method, based on bad theory, worked at least as

well as the other methods, though which worked best, for a particular

disease, depended on the sample size available. Ours was better for

large samples.

It seems that a simple, even a wrong model, can equal or sometimes beat

a better model with fewer parameters. I later found out that Norman

Bailey, at Oxford, had discovered the same thing in a different problem

(multiple regression), but found it so shocking that he did not publish

it.

The point I am making is that "correct theory" does not guarantee better

results in practice, and vice versa. Statistical theory hasn't caught up

with this fact yet, as far as I know.

I will try to explain the difference between the way Sir Harold Jeffreys

and W Edwards Deming *used* probability, which tells you more than what

they say. But it will take time, as I like to be thorough.

Thanks for the information about Joyce Orsini's forthcoming book, and

the review of the book on Bayes Theorem.

I think that there is a lot more to be discovered about Bayes Theorem.

It is certainly a very important practical tool. For example, my email

is scanned for spam by a programme based on Bayes Theorem. But I rather

suspect it is not being used correctly - and still works.

In 1964 I was a Research Fellow, and two of us were investigating

methods of medical diagnosis. In other words, trying to develop

statistical rules for guessing what illness a patient is suffering from,

based on a limited number of tests or symptoms.

We found a paper, written by a computer scientist, that claimed to use

Bayes Theorem in medical diagnosis. But his method did not allow for the

obvious fact that different symptoms are not statistically independent.

We were shocked at such ignorance, and misuse of statistical theory. So

we set out to compare all the best methods we could find, including new

ones we developed ourselves, based on multivariate logistic analysis,

and another based on comparing each case with all the data in a

database.

Sad to say, the "wrong" method, based on bad theory, worked at least as

well as the other methods, though which worked best, for a particular

disease, depended on the sample size available. Ours was better for

large samples.

It seems that a simple, even a wrong model, can equal or sometimes beat

a better model with fewer parameters. I later found out that Norman

Bailey, at Oxford, had discovered the same thing in a different problem

(multiple regression), but found it so shocking that he did not publish

it.

The point I am making is that "correct theory" does not guarantee better

results in practice, and vice versa. Statistical theory hasn't caught up

with this fact yet, as far as I know.

I will try to explain the difference between the way Sir Harold Jeffreys

and W Edwards Deming *used* probability, which tells you more than what

they say. But it will take time, as I like to be thorough.

MANAGEMENT HISTORY 1930

Title: W.
Edwards Deming’s mentor and others who made a significant impact on his views
during the 1920s and 1930s

Author(s): Beth
Blankenship, (Deming Scholar, Hunt Valley, Maryland, USA
and), Peter B. Petersen, (Professor of Management and Organization Theory, Johns Hopkins
University, Baltimore, Maryland, USA)

Citation: Beth
Blankenship, Peter B. Petersen, (1999) "W. Edwards Deming’s mentor and
others who made a significant impact on his views during the 1920s and
1930s", Journal of Management History (Archive), Vol. 5 Iss: 8, pp.454 -
467

David Kerridge to hc/ Oct 16 (2 days ago)

2010.10.18

Dear Hanching Chung

Thanks, the two copies have arrived safely. I just wish I could read

Chinese…

品質標準

david kerridge/wed

首章與要點

Not that the story need be long, but it will take a long while to make it short. Thoreau

And we must never forget Walter Shewhart's fundamental yet

neglected discovery. If a process is under statistical control,

trying harder cannot produce better results, and often makes things

worse. So if rewards *do* make people try harder, and the results

are better, the process was not under control. Why persist with

a bad system? David Kerridge

Shewhart wrote "Progress in modifying our concept of control

has been *and will be* comparatively slow." (My emphasis).

By control in this context he meant, I believe, his whole

approach, not just control charting, though that is a good

place to start.

david kerridge/wed

首章與要點

Not that the story need be long, but it will take a long while to make it short. Thoreau

And we must never forget Walter Shewhart's fundamental yet

neglected discovery. If a process is under statistical control,

trying harder cannot produce better results, and often makes things

worse. So if rewards *do* make people try harder, and the results

are better, the process was not under control. Why persist with

a bad system? David Kerridge

Shewhart wrote "Progress in modifying our concept of control

has been *and will be* comparatively slow." (My emphasis).

By control in this context he meant, I believe, his whole

approach, not just control charting, though that is a good

place to start.

Since
2008, I published one or two books annually on Deming Philosophy. So I think it
might be a good idea to send you 3 books now available (a small part of them
are in English). I can send you several set if you think it is acceptable.
Prof. David Kerridge has a set and you might like his
opinions.

*David*and Sarah

*Kerridge*, „Aristotle's Mistake“. 31. May 2002. Aristotle's Mistake or the

**...**

*"joy in work"*the phrase, originally "pride in work" was amended to "joy" by Deming in 1988, after David Kerridge, professor of statistics at Aberdeen, pointed out that "joy" in labour was found twice in the Book of Ecclesiastes.^{[34][35]}

## The Wisdom of David Kerridge, Part 1

By Davis
Balestracci on Jun 30, 2009 | Categorized under: General

Back to basics

I
discovered a wonderful unpublished paper by David and Sarah Kerridge several
years ago. Its influence on my thinking has been nothing short of profound. As
statistical methods get more and more embedded in everyday organizational
quality improvements, I feel that now is the time to get us “back to
basics”—but a set of basics that is woefully misunderstood, if taught at all.
Professor Kerridge is an academic at the University
of Aberdeen in Scotland, and I
consider him one of the leading Deming thinkers in the world today.Deming distinguished between two types of statistical study, which he called “enumerative” and “analytic.” The key connection for quality improvement is about the way that statistics relates to reality and lays the foundation for a theory of

*using*statistics.

Because everyday processes are usually not static “populations,” the question becomes, “What other knowledge, beyond probability theory, is needed to form a basis for action in the real world?” The perspective from which virtually all college courses are taught—population based—invalidates many of its techniques in a work environment, as opposed to a strictly research environment.

To translate to medicine, there are three kinds of statistics:

**Descriptive .**What can I say about this specific*patient*?**Enumerative.**What can I say about this specific*group*of patients?**Analytic.**What can I say about the*process*that produced this specific group of patients and its results?

*Staphylococcus aureus*, a strain of staph that is resistant to the broad-spectrum antibiotics commonly used to treat infections) in a particular hospital has been reduced by 27 percent—a result that would be extremely desirable if that kind of reduction could be produced in other hospitals, or in public health communities, by using the same methods. However, there are a great many questions to ask before we can act, even if the action is to design an experiment to find out more.

Counting the number of infections in different years is an enumerative problem (defining “acquired infection” and counting them for this specific hospital). Interpreting the change is an analytic problem.

Could the 27-percent reduction be due to chance? If we imagine a set of constant conditions, which would lead, on average, to 100 infections, we can, on the simplest mathematical model (Poisson counts), expect the number we actually see to be anything between 70 and 130. If there were 130 infections one year, and 70 infections the next year, people would think that there had been a great improvement—but this could be just chance. This is the least of our problems.

Some of the infections may be related, as in a temporary outbreak or pandemic. If so, the model is wrong, because it assumes that infections are independent; or the methods of counting might have changed from one year to the next (Are you counting all suspicious infections, or only confirmed cases?). Without knowing about such things we cannot predict from these figures what will happen next year. So if we want to draw the conclusion that the 27-percent reduction is a “real” one, that is, one which will continue in the future, we must use knowledge about the problem that is not given by those figures alone.

Even less can we predict accurately what would happen in a different hospital, or a different country. The causes of infection, or the effect of a change in infection control methods, may be completely different.

So this is the context of the distinction between enumerative and analytic uses of statistics. Some things can be determined by calculation alone, others require the use of judgment or knowledge of the subject, others are almost unknowable. Luckily, your actions to get more information inherently improve the situation, because when you understand the sources of uncertainty, you understand how to reduce it.

Most mathematical statisticians state statistical problems in terms of repeated sampling from the same population. This leads to a very simple mathematical theory, but does not relate to the real needs of the statistical user. You cannot take repeated samples from the exact same population, except in rare cases. It’s a different kind of problem—sampling from an imaginary population.

In every application of statistics we have to decide how far we can trust results obtained at one time, and under one set of circumstances, as a guide to what will happen at some other time, and under new circumstances. Statistical theory, as it is stated in most textbooks, simply analyzes what would happen if we took repeated, strictly random samples, from the same population, under circumstances in which nothing changes with time.

This does tell us something. It tells us what would happen under the most favorable imaginable circumstances. In almost all applications, we do not want a description of the past but a prediction of the future. For this we must rely on theoretical knowledge of the subject, at least as much as on the theory of probability.

So, get your head around these concepts and I’ll give you more of Kerridge’s wisdom in my next column that relates to everyday work.

As you see, it is totally different from the clinical trial mindset in which most physicians have been taught. There is an additional problem, since you shouldn’t have acquired infections (or medical errors, or pressure ulcers), epidemiologists have a tendency to treat any infection as a special cause and want to determine the root cause. This would be helpful in an outbreak, but in terms of everyday work, one usually has to take the view that you are perfectly designed to have infections—you must at least consider the possibility of using a common cause strategy, and “plotting the dots” will tell you which.

For more information on using strategies, see Chapter 8 of my book,

*Data Sanity: A Quantum Leap to Unprecedented Results*(Medical Group Management Association, 2009).

A review of this book is available here: www.qualitydigest.com/inside/quality-insider-news/books-data-sanity-statistics-are-doable.html.

You can order

*Data Sanity*at www5.mgma.com/ecom/Default.aspx?action=INVProductDetails&args=3785&tabid=138.

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