特斯拉：加州事故中自動輔助駕駛系統已啟用特斯拉因螺栓問題召回12.3萬輛Model S轎車 | ||
2018年3月30日 星期五
2018年3月28日 星期三
實篤、Jacob Marschak 之間: team theory實務心理學；理論心理學、經濟學
武者小路實篤- 維基語錄，自由的名人名言錄 - Wikiquote
1885年——1976年
- 一減一是零。人生減愛會剩下什麼？土地減去水分便簡直像沙漠一般。
英文有點微妙：
a theory about the different roles played by members of effectiveteams, that suggests that people with a particular personality are most comfortable in a particular role:
What are the different roles identified in Belbin's team theory?
實務心理學：
Review: In ‘Ready Player One,’ Spielberg Plays the Nostalgia Game
By A. O. SCOTT
The movie, based on Ernest Cline’s best-selling novel, is set in a dystopian future where a virtual video-game reality reigns, and pop-culture callbacks are legion.
在 Deming 的新經濟學，teamwork的強調重點，在組織之間 :
Jacob Marschak、1898年7月23日 - 1977年7月27日
除了讀Wikipedia 關於Jacob Marschak項目，我還是去讀比較專業的經濟學辭典中的Jacob Marschak 項目，由其合著者Roy Radner 撰寫。
- Economic Theory of Teams, with Roy Radner, 1972.（『チームの経済理論』）
書，獻給老友；我們也須要：對理性的"信仰"，對人間溫情的渴求。
To the Memory of
Jacob Marschak,
who had an unshakeable faith in
human reason, and unmatched
store of human warmth.
Jacob Marschak,
who had an unshakeable faith in
human reason, and unmatched
store of human warmth.
Audiovisual Materials
2018年3月26日 星期一
Google Street View could be the demographer’s new best friend.
Google Street View can provide a relatively quick, large-scale way to look at people's transportation patterns, the effect of changes in transport policy, and even the exercise habits of the population.
2018年3月19日 星期一
習近平治下官僚體系的危險隱患
中國主席習近平要求北京減少人口，他的親信便下令剷平數萬名民工的家園。習近平要求中國北方各省減少霧霾，於是幹部們拆掉了暖氣和煤爐，讓居民在家中挨凍。
正如近期這些案例所表明的，習近平令人生畏的權力可能會削弱有效的政策；過度熱忱的底層官員為了達到或超額完成任務而緊急行動起來，往往亦會導致過度和混亂，從而引發公眾憤怒。
2018年3月17日 星期六
Reaching human parity 等測試準則
Reaching new records in speech recognition - Watson - IBM
https://www.ibm.com/blogs/watson/.../reaching-new-records-in-speech-recognition/
Mar 7, 2017 - Reaching human parity – meaning an error rate on par with that of two humans speaking – has long been the ultimate industry goal. Others in the industry are chasing this milestone alongside us, and some have recently claimed reaching 5.9 percent as equivalent to human parity…but we're not popping ...
AI translation from Chinese to English:
Microsoft now does it with news articles as well as humans do. (Via TechCrunch)
Microsoft now does it with news articles as well as humans do. (Via TechCrunch)
2018年3月1日 星期四
Remembering Prof. David Kerridge
我看過愛丁堡大學校友會的The Carlyle Circle
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
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。
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
>independently discovered it).
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.
Yes, I have attached it in Rich Text Format, so that it keeps some of
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.
Sorry, I thought that Rich Text Format was universal. Here it is in
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
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,
I will do my best, but this is a big question, and will take time to
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,
MANAGEMENT HISTORY 1930
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:
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.
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. In Quality or else: the revolution in world business Lloyd 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, 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.”
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），
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/
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灣戴明圈
Dear Hanching Chung
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. 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.
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."
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 David,
Dear David,
5/26/11
Scientific Inference by Sir Harold Jeffreys
Dear
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
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 Scientific Inference - Harold Jeffreys (The Google Books)
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 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,
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?
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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