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    Landa, Edward 2014. The Soil Underfoot.


    Giocoli, Nicola 2013. From Wald to Savage:Homo EconomicusBecomes a Bayesian Statistician. Journal of the History of the Behavioral Sciences, Vol. 49, Issue. 1, p. 63.


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W.S. Gosset and Some Neglected Concepts in Experimental Statistics: Guinnessometrics II*

  • Stephen T. Ziliak (a1)
  • DOI: http://dx.doi.org/10.1017/S1931436100001632
  • Published online: 01 June 2012
Abstract
Abstract

Student's exacting theory of errors, both random and real, marked a significant advance over ambiguous reports of plant life and fermentation asserted by chemists from Priestley and Lavoisier down to Pasteur and Johannsen, working at the Carlsberg Laboratory. One reason seems to be that William Sealy Gosset (1876–1937) aka “Student” – he of Student's t-table and test of statistical significance – rejected artificial rules about sample size, experimental design, and the level of significance, and took instead an economic approach to the logic of decisions made under uncertainty. In his job as Apprentice Brewer, Head Experimental Brewer, and finally Head Brewer of Guinness, Student produced small samples of experimental barley, malt, and hops, seeking guidance for industrial quality control and maximum expected profit at the large scale brewery. In the process Student invented or inspired half of modern statistics. This article draws on original archival evidence, shedding light on several core yet neglected aspects of Student's methods, that is, Guinnessometrics, not discussed by Ronald A. Fisher (1890–1962). The focus is on Student's small sample, economic approach to real error minimization, particularly in field and laboratory experiments he conducted on barley and malt, 1904 to 1937. Balanced designs of experiments, he found, are more efficient than random and have higher power to detect large and real treatment differences in a series of repeated and independent experiments. Student's world-class achievement poses a challenge to every science. Should statistical methods – such as the choice of sample size, experimental design, and level of significance – follow the purpose of the experiment, rather than the other way around? (JEL classification codes: C10, C90, C93, L66)

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Journal of Wine Economics
  • ISSN: 1931-4361
  • EISSN: 1931-437X
  • URL: /core/journals/journal-of-wine-economics
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