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m →Statistical terms: clean up, References after punctuation per WP:REFPUNC and WP:CITEFOOT using AWB (9345)
m moved Gordon's quotation about Tukey to under Statistical Practice header, since it was not said by Tukey
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Though he believed in the utility of separating the two types of analysis, he pointed out that sometimes, especially in [[natural science]], this was problematic and termed such situations [[uncomfortable science]].
Though he believed in the utility of separating the two types of analysis, he pointed out that sometimes, especially in [[natural science]], this was problematic and termed such situations [[uncomfortable science]].


⚫
A D Gordon <!-- not A.D. Gordon -->offered the following summary of Tukey's principles for statistical practice:
⚫
:... the usefulness and limitation of mathematical statistics; the importance of having methods of statistical analysis that are robust to violations of the assumptions underlying their use; the need to amass experience of the behaviour of specific methods of analysis in order to provide guidance on their use; the importance of allowing the possibility of data's influencing the choice of method by which they are analysed; the need for statisticians to reject the role of 'guardian of proven truth', and to resist attempts to provide once-for-all solutions and tidy over-unifications of the subject; the iterative nature of data analysis; implications of the increasing power, availability and cheapness of computing facilities; the training of statisticians.
== Statistical terms ==
== Statistical terms ==
Tukey coined many statistical terms that have become part of common usage, but the two most famous coinages attributed to him were related to computer science.
Tukey coined many statistical terms that have become part of common usage, but the two most famous coinages attributed to him were related to computer science.
Line 61: Line 63:
:# Some graph paper (or transparencies, or both).
:# Some graph paper (or transparencies, or both).
: No catalogue of techniques can convey a willingness to look for what can be seen, whether or not anticipated. Yet this is at the heart of exploratory data analysis. The graph paper - and transparencies - are there, not as a technique, but rather as recognition that the picture-examining eye is the best finder we have of the wholly unanticipated.
: No catalogue of techniques can convey a willingness to look for what can be seen, whether or not anticipated. Yet this is at the heart of exploratory data analysis. The graph paper - and transparencies - are there, not as a technique, but rather as recognition that the picture-examining eye is the best finder we have of the wholly unanticipated.
⚫
* A D Gordon <!-- not A.D. Gordon -->offered the following summary of Tukey's principles for statistical practice:
⚫
:... the usefulness and limitation of mathematical statistics; the importance of having methods of statistical analysis that are robust to violations of the assumptions underlying their use; the need to amass experience of the behaviour of specific methods of analysis in order to provide guidance on their use; the importance of allowing the possibility of data's influencing the choice of method by which they are analysed; the need for statisticians to reject the role of 'guardian of proven truth', and to resist attempts to provide once-for-all solutions and tidy over-unifications of the subject; the iterative nature of data analysis; implications of the increasing power, availability and cheapness of computing facilities; the training of statisticians.
* Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.
* Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.
* Once upon a time statisticians only explored. Then they learned to confirm exactly - to confirm a few things exactly, each under very specific circumstances. As they emphasized exact confirmation, their techniques inevitably became less flexible. The connection of the most used techniques with past insights was weakened. Anything to which a confirmatory procedure was not explicitly attached was decried as 'mere descriptive statistics', no matter how much we had learned from it.
* Once upon a time statisticians only explored. Then they learned to confirm exactly - to confirm a few things exactly, each under very specific circumstances. As they emphasized exact confirmation, their techniques inevitably became less flexible. The connection of the most used techniques with past insights was weakened. Anything to which a confirmatory procedure was not explicitly attached was decried as 'mere descriptive statistics', no matter how much we had learned from it.

Revision as of 16:07, 24 July 2013

John Tukey
John Wilder Tukey
Born(1915-06-16)June 16, 1915
New Bedford, Massachusetts, USA
DiedJuly 26, 2000(2000-07-26) (aged 85)
New Brunswick, New Jersey
NationalityAmerican
Alma materBrown University
Princeton University
Known forFFT algorithm
Box plot
Exploratory Data Analysis
Coining the term 'bit'
AwardsSamuel S. Wilks Award (1965)
National Medal of Science (USA) in Mathematical, Statistical, and Computational Sciences (1973)
Shewhart Medal (1976)
IEEE Medal of Honor (1982)
Deming Medal (1982)
James Madison Medal (1984)
Foreign Member of the Royal Society (1991)
Scientific career
FieldsMathematician
InstitutionsBell Labs
Princeton University
Doctoral advisorSolomon Lefschetz
Doctoral studentsArthur Dempster
Leo Goodman
Paul Meier
Frederick Mosteller
Kai Lai Chung

John Wilder Tukey ForMemRS[1] (/ˈtjuːki/; June 16, 1915 – July 26, 2000) was an American mathematician best known for development of the FFT algorithm and box plot.

Biography

Tukey was born in New Bedford, Massachusetts in 1915, and obtained a B.A. in 1936 and M.Sc. in 1937, in chemistry, from Brown University, before moving to Princeton University where he received a Ph.D. in mathematics.[2]

During World War II, Tukey worked at the Fire Control Research Office and collaborated with Samuel Wilks and William Cochran. After the war, he returned to Princeton, dividing his time between the university and AT&T Bell Laboratories.

Among many contributions to civil society, Tukey served on a committee of the American Statistical Association that produced a report challenging the conclusions of the Kinsey Report, Statistical Problems of the Kinsey Report on Sexual Behavior in the Human Male.

He was awarded the IEEE Medal of Honor in 1982 "For his contributions to the spectral analysis of random processes and the fast Fourier transform (FFT) algorithm."

Tukey retired in 1985. He died in New Brunswick, New Jersey on July 26, 2000.

Scientific contributions

Early in his career Tukey worked on developing statistical methods for computers at Bell Labs where he invented the term "bit".[3]

His statistical interests were many and varied. He is particularly remembered for his development with James Cooley of the Cooley–Tukey FFT algorithm. In 1970, he contributed significantly to what is today known as the jackknife estimation—also termed Quenouille-Tukey jackknife. He introduced the box plot in his 1977 book, "Exploratory Data Analysis".

Tukey's range test, the Tukey lambda distribution, Tukey's test of additivity and Tukey's lemma all bear his name. He is also the creator of several little-known methods such as the trimean and median-median line, an easier alternative to linear regression.

In 1974, he developed, with Jerome H. Friedman, the concept of the projection pursuit.[4]

Statistical practice

He also contributed to statistical practice and articulated the important distinction between exploratory data analysis and confirmatory data analysis, believing that much statistical methodology placed too great an emphasis on the latter.

Though he believed in the utility of separating the two types of analysis, he pointed out that sometimes, especially in natural science, this was problematic and termed such situations uncomfortable science.

A D Gordon offered the following summary of Tukey's principles for statistical practice:

... the usefulness and limitation of mathematical statistics; the importance of having methods of statistical analysis that are robust to violations of the assumptions underlying their use; the need to amass experience of the behaviour of specific methods of analysis in order to provide guidance on their use; the importance of allowing the possibility of data's influencing the choice of method by which they are analysed; the need for statisticians to reject the role of 'guardian of proven truth', and to resist attempts to provide once-for-all solutions and tidy over-unifications of the subject; the iterative nature of data analysis; implications of the increasing power, availability and cheapness of computing facilities; the training of statisticians.

Statistical terms

Tukey coined many statistical terms that have become part of common usage, but the two most famous coinages attributed to him were related to computer science.

While working with John von Neumann on early computer designs, Tukey introduced the word "bit" as a contraction of "binary digit".[5] The term "bit" was first used in an article by Claude Shannon in 1948.

In 2000, Fred Shapiro, a librarian at the Yale Law School, published a letter revealing that Tukey's 1958 paper "The Teaching of Concrete Mathematics"[6] contained the earliest known usage of the term "software" found in a search of JSTOR's electronic archives, predating the OED's citation by two years.[7] This led many to credit Tukey with coining the term, particularly in obituaries published that same year,[8] although Tukey never claimed credit for any such coinage. In 1995, Paul Niquette claimed he had originally coined the term in October 1953, although he could not find any documents supporting his claim.[9] The earliest known publication of the term "software" in an engineering context was in August 1953 by Richard R. Carhart, in a Rand Corporation Research Memorandum.[10]

Quotes

  • If we need a short suggestion of what exploratory data analysis is, I would suggest that
  1. It is an attitude AND
  2. A flexibility AND
  3. Some graph paper (or transparencies, or both).
No catalogue of techniques can convey a willingness to look for what can be seen, whether or not anticipated. Yet this is at the heart of exploratory data analysis. The graph paper - and transparencies - are there, not as a technique, but rather as recognition that the picture-examining eye is the best finder we have of the wholly unanticipated.
  • Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.
  • Once upon a time statisticians only explored. Then they learned to confirm exactly - to confirm a few things exactly, each under very specific circumstances. As they emphasized exact confirmation, their techniques inevitably became less flexible. The connection of the most used techniques with past insights was weakened. Anything to which a confirmatory procedure was not explicitly attached was decried as 'mere descriptive statistics', no matter how much we had learned from it.
  • There is no data that can be displayed in a pie chart, that cannot be displayed BETTER in some other type of chart.

Publications

  • Andrews, David F; Peter J Bickel; Frank R Hampel; Peter J Huber; W H Rogers & John W Tukey (1972). Robust estimates of location: survey and advances. Princeton University Press. ISBN 0-691-08113-1. OCLC 369963.{{cite book}}: CS1 maint: multiple names: authors list (link)
  • Basford, Kaye E & John W Tukey (1998). Graphical analysis of multiresponse data. Chapman & Hall/CRC. ISBN 0-8493-0384-2. OCLC 154674707.
  • Blackman, R B & John W Tukey (1959). The measurement of power spectra from the point of view of communications engineering. Dover Publications. ISBN 0-486-60507-8.
  • Cochran, William G; Frederick Mosteller & John W Tukey (1954). Statistical problems of the Kinsey report on sexual behavior in the human male. Journal of the American Statistical Association.{{cite book}}: CS1 maint: multiple names: authors list (link)
  • Hoaglin, David C; Frederick Mosteller & John W Tukey (eds) (1983). Understanding Robust and Exploratory Data Analysis. Wiley. ISBN 0-471-09777-2. OCLC 8495063. {{cite book}}: |last= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Hoaglin, David C; Frederick Mosteller & John W Tukey (eds) (1985). Exploring Data Tables, Trends and Shapes. Wiley. ISBN 0-471-09776-4. OCLC 11550398. {{cite book}}: |last= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Hoaglin, David C; Frederick Mosteller & John W Tukey (eds) (1991). Fundamentals of exploratory analysis of variance. Wiley. ISBN 0-471-52735-1. OCLC 23180322. {{cite book}}: |last= has generic name (help)CS1 maint: multiple names: authors list (link)
  • Morganthaler, Stephan & John W Tukey (eds) (1991). Configural polysampling: a route to practical robustness. Wiley. ISBN 0-471-52372-0. OCLC 22381036. {{cite book}}: |last= has generic name (help)
  • Mosteller, Frederick & John W Tukey (1977). Data analysis and regression : a second course in statistics. Addison-Wesley. ISBN 0-201-04854-X. OCLC 3235470.
  • Tukey, John W (1940). Convergence and Uniformity in Topology. Princeton University Press. ISBN 0-691-09568-X. OCLC 227948615.
  • Tukey, John W (1977). Exploratory Data Analysis. Addison-Wesley. ISBN 0-201-07616-0. OCLC 3058187.
  • Tukey, John W; Ian C Ross; Verna Bertrand (1973–). Index to statistics and probability. R & D Press. ISBN 0-88274-001-6. OCLC 745715. {{cite book}}: Check date values in: |year= (help); Invalid |display-authors=4 (help)CS1 maint: year (link)
The collected works of John W Tukey, edited by William S Cleveland
About John Tukey

See also

Notes

  1. ^ Attention: This template ({{cite doi}}) is deprecated. To cite the publication identified by doi:10.1098/rsbm.2003.0032, please use {{cite journal}} (if it was published in a bona fide academic journal, otherwise {{cite report}} with |doi=10.1098/rsbm.2003.0032 instead.
  2. ^ "John Tukey". IEEE Global History Network. IEEE. Retrieved 18 July 2011.
  3. ^ Claude Shannon (1948). "Bell Systems Technical Journal". Bell Systems Technical Journal.
  4. ^ J. H. Friedman and J. W. Tukey (1974). "A Projection Pursuit Algorithm for Exploratory Data Analysis" (PDF). IEEE Transactions on Computers. C-23 (9): 881–890. doi:10.1109/T-C.1974.224051. ISSN 0018-9340. {{cite journal}}: Unknown parameter |month= ignored (help)
  5. ^ The origin of the 'bit'
  6. ^ J.W. Tukey, "The Teaching of Concrete Mathematics," Amer. Mathematical Monthly, vol. 65, pp. 1–9, 1958: "Today the “software” comprising the carefully planned interpretive routines, compilers, and other aspects of automative programming are at least as important to the modern electronic calculator as its “hardware” of tubes, transistors, wires, tapes, and the like."
  7. ^ Shapiro, Fred (2000). "Origin of the Term Software: Evidence from the JSTOR Electronic Journal Archive" (PDF). IEEE Annals of the History of Computing. 22 (2): 69–71. Retrieved 25 June 2013.
  8. ^ Leonhardt, David (28 July 2000). "John Tukey, 85, Statistician; Coined the Word 'Software'". New York Times. Retrieved 24 September 2012.
  9. ^ Niquette, P. (2006) Softword: Provenance for the Word 'Software'
  10. ^ Carhart, Richard (1953). A survey of the current status of the electronic reliability problem. Santa Monica, CA: Rand Corporation. p. 65. It will be recalled from Sec. 1.6 that the term personnel was defined to include people who come into direct contact with the hardware, from production to field use, i.e., people who assemble, inspect, pack, ship, handle, install, operate and maintain electronic equipment. In any of these phases personnel failures may result in unoperational gear. As with the hardware factors, there is almost no quantitative data concerning these software or human factors in reliability: How many faults are caused by personnel, why they occur, and what can be done to remove the errors.
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