Difference between revisions of "Timeline of experiment design"

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| 1939 || || Publication by Bose and Nair underlie the concept of ''{{w|association scheme}}''.<ref>{{citation| last1=Bose|first1=R.&nbsp;C.|authorlink1=R. C. Bose|first2= K.&nbsp;R.|last2= Nair|title= Partially balanced incomplete block designs|journal= [[Sankhya (journal)|Sankhyā]]|volume= 4|year=1939|pages= 337–372}}</ref>  
 
| 1939 || || Publication by Bose and Nair underlie the concept of ''{{w|association scheme}}''.<ref>{{citation| last1=Bose|first1=R.&nbsp;C.|authorlink1=R. C. Bose|first2= K.&nbsp;R.|last2= Nair|title= Partially balanced incomplete block designs|journal= [[Sankhya (journal)|Sankhyā]]|volume= 4|year=1939|pages= 337–372}}</ref>  
 
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| 1950 || || {{w|Gertrude Mary Cox}} and {{w|William Gemmell Cochran}} publish the book ''Experimental Designs'', which would become the major reference work on the design of experiments for statisticians for years afterwards.
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| 1951 || || The {{w|response surface methodology}} method is introduced by {{w|George E. P. Box}} and K. B. Wilson.
 
| 1951 || || The {{w|response surface methodology}} method is introduced by {{w|George E. P. Box}} and K. B. Wilson.
 
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Revision as of 17:36, 13 March 2020

This is a timeline of FIXME.

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Time period Development summary More details

Full timeline

Year Event type Details
1700 Korean mathematician Choi Seok-jeong is the first to publish an example of Latin squares of order nine, in order to construct a magic square, predating Leonhard Euler by 67 years.[1] Latin squares are used in combinatorics and in experimental design.
1784 The first blinded experiment is conducted by the French Academy of Sciences to investigate the claims of mesmerism as proposed by Franz Mesmer. In the experiment, researchers blindfolded mesmerists and asked them to identify objects that the experimenters had previously filled with "vital fluid". The subjects are unable to do so.
1979 The latin hypercube sampling is described by Michael McKay of Los Alamos National Laboratory in 1979.[2]
1817 The first blinded experiment recorded outside of a scientific setting compares the musical quality of a Stradivarius violin to one with a guitar-like design. A violinist plays each instrument while a committee of scientists and musicians listen from another room so as to avoid prejudice.[3][4]
1918 Analysis of variance. Ronald Fisher introduces the term variance and proposes its formal analysis in his article The Correlation Between Relatives on the Supposition of Mendelian Inheritance.[5]
1921 Ronald Fisher publishes his first application of the analysis of variance.[6]
1923 The first randomization model is published in Polish by Jerzy Neyman.[7]
1925 Analysis of variance becomes widely known after being included in Ronald Fisher's book Statistical Methods for Research Workers.
1925 British statistician Ronald Fisher publishes Statistical Methods for Research Workers.
1926 Factorial experiment. Ronald Fisher argues that "complex" designs (such as factorial designs) are more efficient than studying one factor at a time.[8]
1939 Publication by Bose and Nair underlie the concept of association scheme.[9]
1950 Gertrude Mary Cox and William Gemmell Cochran publish the book Experimental Designs, which would become the major reference work on the design of experiments for statisticians for years afterwards.
1951 The response surface methodology method is introduced by George E. P. Box and K. B. Wilson.
1952 Bose and Shimamoto introduce the term association scheme.[10]
1960 "In statistics, Box–Behnken designs are experimental designs for response surface methodology, devised by George E. P. Box and Donald Behnken in 1960"
1961 Leslie Kish introduces the term design effect.[11]
1982 Factorial experiment. "In his book, Improving Almost Anything: Ideas and Essays, statistician George Box gives many examples of the benefits of factorial experiments."[12]
1986 "The start of experimental benchmarking in social science is often attributed to Robert LaLonde. In 1986 he found that findings of econometric procedures assessing the effect of an employment program on trainee earnings did not recover the experimental findings."[13]
1991 "International Data Farming Workshop 1 occurred in 1991, and since then 16 more workshops have taken place. The workshops have seen a diverse array of representation from participating countries, such as Canada, Singapore, Mexico, Turkey, and the United States."[14]
1998 Stat-Ease releases its first version of Design–Expert, a statistical software package specifically dedicated to performing design of experiments.[15]
2002 The terms exploratory thought and confirmatory thought are introduced by social psychologist Jennifer Lerner and psychology professor Philip Tetlock in their book Emerging Perspectives in Judgment and Decision Making.[16]
2009 Adversarial collaboration is recommended by Daniel Kahneman[17] and others as a way of resolving contentious issues in fringe science, such as the existence or nonexistence of extrasensory perception.[18]

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References

  1. Colbourn, Charles J.; Dinitz, Jeffrey H. Handbook of Combinatorial Designs (2nd ed.). CRC Press. p. 12. ISBN 9781420010541. Retrieved 28 March 2017. 
  2. McKay, M.D.; Beckman, R.J.; Conover, W.J. (May 1979). "A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code". Technometrics. American Statistical Association. 21 (2): 239–245. ISSN 0040-1706. JSTOR 1268522. OSTI 5236110. doi:10.2307/1268522. 
  3. Fétis F (1868). Biographie Universelle des Musiciens et Bibliographie Générale de la Musique, Tome 1 (Second ed.). Paris: Firmin Didot Frères, Fils, et Cie. p. 249. Retrieved 2011-07-21. 
  4. Dubourg G (1852). The Violin: Some Account of That Leading Instrument and its Most Eminent Professors... (Fourth ed.). London: Robert Cocks and Co. pp. 356–357. Retrieved 2011-07-21. 
  5. The Correlation Between Relatives on the Supposition of Mendelian Inheritance. Ronald A. Fisher. Philosophical Transactions of the Royal Society of Edinburgh. 1918. (volume 52, pages 399–433)
  6. On the "Probable Error" of a Coefficient of Correlation Deduced from a Small Sample. Ronald A. Fisher. Metron, 1: 3–32 (1921)
  7. Scheffé (1959, p 291, "Randomization models were first formulated by Neyman (1923) for the completely randomized design, by Neyman (1935) for randomized blocks, by Welch (1937) and Pitman (1937) for the Latin square under a certain null hypothesis, and by Kempthorne (1952, 1955) and Wilk (1955) for many other designs.")
  8. Fisher, Ronald (1926). "The Arrangement of Field Experiments" (PDF). Journal of the Ministry of Agriculture of Great Britain. London, England: Ministry of Agriculture and Fisheries. 33: 503–513. 
  9. Bose, R. C.; Nair, K. R. (1939), "Partially balanced incomplete block designs", Sankhyā, 4: 337–372 
  10. Bose, R. C.; Shimamoto, T. (1952), "Classification and analysis of partially balanced incomplete block designs with two associate classes", Journal of the American Statistical Association, 47: 151–184, doi:10.1080/01621459.1952.10501161 
  11. Kish, Leslie (1965). "Survey Sampling". New York: John Wiley & Sons, Inc. ISBN 0-471-10949-5. 
  12. George E.P., Box (2006). Improving Almost Anything: Ideas and Essays (Revised ed.). Hoboken, New Jersey: Wiley. ASIN B01FKSM9VY. 
  13. LaLonde, Robert (1986). "Evaluating the Econometric Evaluations of Training Programs with Experimental Data". American Economic Review. 4 (76): 604–620. 
  14. Horne, G., & Schwierz, K. (2008). Data farming around the world overview. Paper presented at the 1442-1447. doi:10.1109/WSC.2008.4736222
  15. Li He, "Design of Experiments Software, DOE software", The Chemical Information Network, July 17, 2003.
  16. Schneider, ed. by Sandra L.; Shanteau, James (2003). Emerging perspectives on judgment and decision research. Cambridge [u.a.]: Cambridge Univ. Press. pp. 438–9. ISBN 052152718X. 
  17. Kahneman, Daniel; Klein, Gary. Conditions for intuitive expertise: A failure to disagree. American Psychologist, Vol 64(6), Sep 2009, 515-526. doi: 10.1037/a0016755
  18. Wagenmakers, E.-J., Wetzels, R., Borsboom, D., & van der Maas, H. L. J. (2010). Why psychologists must change the way they analyze their data: The case of psi.