Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-27T16:16:38.784Z Has data issue: false hasContentIssue false
  • English
  • Français

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

Published online by Cambridge University Press:  08 June 2012

Stephen T. Ziliak
Stephen T. Ziliak
Affiliation:
Roosevelt University, Chicago. 430 S. Michigan Ave, Chicago, IL 60605. e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

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)

Type
Articles
Information
Journal of Wine Economics , Volume 6 , Issue 2 , Autumn 2011 , pp. 252 - 277
Copyright
Copyright © American Association of Wine Economists 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Banerjee, A. and Duflo, E. (2011). Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty. New York: Public Affairs.Google Scholar
Beaven, E.S. (1947). Barley: Fifty Years of Observation and Experiment. London: Duckworth.Google Scholar
Brown, H.T., (ed.) (1903). Transactions of the Guinness Research Laboratory, Vol. I, Part I. Dublin: Arthur Guinness, Son and Co., Ltd.Google Scholar
Bruhn, M. and McKenzie, D. (2009). In pursuit of balance: randomization in practice in development economics. American Economic Journal: Applied Economics, 4, 200–232.Google Scholar
Dennison, S.R. and MacDonagh, O. (1998). Guinness 1886–1939. Cork: Cork University Press.Google Scholar
Duflo, E., Glennerster, R. and Kremer, M. (2006). Using Randomization in Development Economics Research: A Toolkit. December 12, 2006, J-PAL Poverty Action Lab, MIT.CrossRefGoogle Scholar
Fisher, I. (1926). Prohibition at its Worst. New York: The Macmillan Company.Google Scholar
Fisher, R.A. (1925a [1941]). Statistical Methods for Research Workers. New York: G.E. Stechart and Co.Google Scholar
Fisher, R.A. (1926). Arrangement of Field Experiments. Journal of Ministry of Agriculture, 23, 503–513.Google Scholar
Fisher, R.A. (1935). The Design of Experiments, Edinburgh: Oliver & Boyd. Reprinted in eight editions and in at least four different languages.Google Scholar
Fisher, R.A. (1939). Student. Annals of Eugenics, 9, 1–9.CrossRefGoogle Scholar
Fisher, R.A. and Yates, F. (1938 [1963]). Statistical Tables for Biological, Agricultural and Medical Research, Edinburgh: Oliver and Boyd. Sixth edition.Google Scholar
Friedman, M. (1953). The effects of a full-employment policy on economic stability: a formal analysis. In: Friedman, M., Essays in Positive Economics. Chicago: University of Chicago Press, 117–132.Google Scholar
Geison, G.L. (1995). The Private Science of Louis Pasteur. Princeton: Princeton University Press.Google Scholar
Gosset, W.S. [see “Student”, below] (1904). The Application of the ‘Law of Error’ to the Work of the Brewery. Laboratory Report, 8, Arthur Guinness & Son, Ltd., Diageo, Guinness Archives, 3–16 and unnumbered appendix.Google Scholar
Gosset, W.S. (1905). Letter from W.S. Gosset to K. Pearson, Guinness Archives, GDB/BRO/1102 (partially reprinted in Pearson (1939), 215–216).Google Scholar
Gosset, W.S. (1908). The present position of our knowledge of the connection between life and hops in the experimental brewery. Laboratory Report, 10, Arthur Guinness & Son, Ltd., Diageo, Guinness Archives, 137–150.Google Scholar
Gosset, W.S. (1909). The brewing of the experimental hop farm hops, 1907 Crop (Part II), Together with a note on the present method of hop analysis. Laboratory Report, 10, Arthur Guinness & Son, Ltd., Diageo, Guinness Archives, 202–220.Google Scholar
Gosset, W.S. (1936). Co-operation in large-scale experiments. Supplement to the Journal of the Royal Statistical Society, 3, 115–36.Google Scholar
Gosset, W.S. (1962). Letters of William Sealy Gosset to R.A. Fisher. Vols. 1–5, Eckhart Library, University of Chicago. Private circulation.Google Scholar
Harrison, G. (2011). Randomization and its discontents. Journal of African Economies, 20, 626–652.CrossRefGoogle Scholar
Heckman, J.J. and Vytlacil, E.J. (2007). Econometric evaluation of social programs, Part I: causal models, structural models and econometric policy evaluation. In: Heckman, J.J. and Leamer, E. (eds.), Handbook of Econometrics 6B. Amsterdam: Elsevier, 4836–5143.Google Scholar
Herberich, D.H., Levitt, S.D. and List, J.A. (2009). Can field experiments return agricultural economics to the glory days? American Journal of Agricultural Economics, 91, 1259–1265.CrossRefGoogle Scholar
Holmes, F.L. (1985). Lavoisier and the Chemistry of Life: An Exploration of Scientific Creativity. Madison: University of Wisconsin Press.Google Scholar
Holter, H. and Møller, K.M. (eds.) (1976). The Carlsberg Laboratory, 1876–1976, Copenhagen: Rhodos and the Carlsberg Foundation.Google Scholar
Jeffreys, H. 1939 [1961]. Theory of Probability, London: Oxford University Press.Google Scholar
Karlan, D. and List, J. (2007). Does price matter in charitable giving? Evidence from a large-scale natural field experiment. American Economic Review, 97, 1774–1793.CrossRefGoogle Scholar
Lanham, R.A. (1991). A Handlist of Rhetorical Terms. Los Angeles: University of California Press.CrossRefGoogle Scholar
Leonard, A. (2009). Celebrate the history of statistics: drink a Guinness. How a master brewer forged new ground in the quantitative progress of science. Salon, September 28. http://mobile.salon.com/tech/htww/2009/09/28/guinessometrics/index.htmlGoogle Scholar
Levitt, S.D. and List, J.A. (2009). Field experiments in economics: the past, the present, and the future. European Economic Review, 53, 1–18.CrossRefGoogle Scholar
McCloskey, D.N. and Ziliak, S.T. (1996). The standard error of regressions. Journal of Economic Literature, 34, 97–114.Google Scholar
McCloskey, D.N. and Ziliak, S.T. (2010). Brief of Amici Curiae By Statistics Experts Professors Deirdre N. McCloskey and Stephen T. Ziliak in Support of Respondents (Vol. No. 09–1156, Matrixx v. Siracusano, p. 22), Washington DC: Supreme Court of the United States. Edward Labaton et al., Counsel of Record (ed.)Google Scholar
McMullen, L. (1950). The sources and nature of statistical information in special fields of statistics. Journal of the Royal Statistical Society, Series A (General), 113, 230–237.CrossRefGoogle Scholar
Mercer, W.B. and Hall, A.D. (1911). The experimental error of yield trials. Journal of Agricultural Science, 4, 107–127.CrossRefGoogle Scholar
Neyman, J. and Pearson, E.S. (1938). Note on some points on ‘Student's’ paper on ‘comparison between balanced and random arrangements of field plots. Biometrika, 29, 379–88.CrossRefGoogle Scholar
Nye, J. (2007). War, Wine, and Taxes. Princeton: Princeton University Press.CrossRefGoogle Scholar
Pasteur, L. (1879). Studies of Fermentation: The Diseases of Beer – Their Causes and the Means of Preventing Them. London: Macmillan. (Faulkner, F. and Robb, D. Constable, transl.)Google Scholar
Pearson Papers (Containing files on K., Pearson, E.S., Pearson, W.S., Gosset, R.A., Fisher, and J., Neyman), University College London (UCL), Special Collections Library.Google Scholar
Pearson, E.S. (1938). Some aspects of the problem of randomization: II. An illustration of “Student's” inquiry into the effect of “balancing” in agricultural experiment. Biometrika, 30, 159–179.Google Scholar
Pearson, E.S. (1939). ‘Student’ as statistician. Biometrika, 30, 210–50.Google Scholar
Pearson, E.S. (1968). Studies in the history of probability and statistics. XX: some early correspondence between W.S. Gosset, R.A. Fisher and Karl Pearson, with notes and comments. Biometrika, 55, 445–57.Google Scholar
Pearson, E.S. (1990) [posthumous]. ‘Student’: A Statistical Biography of William Sealy Gosset. Oxford: Clarendon Press. R.L., Plackett (ed.), with the assistance of Barnard G.CrossRefGoogle Scholar
Press, S.J. (2003). Subjective and Objective Bayesian Statistics. New York: Wiley.Google Scholar
Priestley, J. (1806). Memoirs of Dr. Joseph Priestley, to the Year 1795, Written by Himself. London: J. Johnson.Google Scholar
Rothman, K.J., Greenland, S. and Lash, T.L. (2008). Modern Epidemiology, Philadelphia: Lippincott, Williams & Wilkins.Google Scholar
Savage, L.J. (1954). The Foundations of Statistics. New York: Dover.Google Scholar
Savage, L.J. (1971). [1976 posthumous]. On re-reading R.A. Fisher. Annals of Statistics, 4, 441–500.Google Scholar
Schabas, M. (2006). The Natural Origins of Economics. Chicago: University of Chicago Press.Google Scholar
Schofield, R.E. (1966). A Scientific Autobiography of Joseph Priestley, 1733–1804: Selected Scientific Correspondence, with Commentary. Cambridge, MA: The MIT Press.Google Scholar
Stewart, G.G. (2009). The Horace Brown Medal Lecture: forty years of brewing research. Journal of the Institute of Brewing, 115, 3–29.CrossRefGoogle Scholar
Student [see also: Gosset, W.S.] (1907). On the error of counting with a haemacytometer. Biometrika, 5, 351–60.Google Scholar
Student, (1908a). The probable error of a mean. Biometrika, 6, 1–24.CrossRefGoogle Scholar
Student, (1908b). The probable error of a correlation coefficient. Biometrika, 6, 300–310.CrossRefGoogle Scholar
Student, (1911). Appendix to Mercer and Hall's paper on ‘the experimental error of field trials’. Journal of Agricultural Science, 4, 128–131.Google Scholar
Student, (1923). On testing varieties of cereals. Biometrika, 15, 271–293.CrossRefGoogle Scholar
Student, (1925). New tables for testing the significance of observations. Metron, 5, 105–108.Google Scholar
Student, (1931a). The Lanarkshire milk experiment. Biometrika, 23, 398–406.CrossRefGoogle Scholar
Student, (1931b). On the ‘z’ test. Biometrika, 23, 407–8.CrossRefGoogle Scholar
Student, (1931c). Yield Trials. Bailliere's Encyclopedia of Scientific Agriculture, 1342–1360; Reprinted: pp. 150–168 in Pearson E.S. and Wishart|J. (eds.) (194). Student's Collected Papers. London: Biometrika Office.Google Scholar
Student, (1938, posthumous). Comparison between balanced and random arrangements of field plots. Biometrika, 29, 363–78.CrossRefGoogle Scholar
Student, (1942, posthumous). Student's Collected Papers. London: Biometrika Office. Pearson, E.S. and Wishart, J. (eds.).Google Scholar
Swinnen, J. and Vandemoortele, T. (2011). Beeronomics: the economics of beer and brewing. In: Swinnen, J.F.M. (ed.), The Economics of Beer. Oxford: Oxford University Press, 335–355.CrossRefGoogle Scholar
Zellner, A. (2005). Statistics, Econometrics, and Forecasting. The Stone Lectures in Economics. Cambridge, UK: Cambridge University Press.Google Scholar
Zellner, A. (2010). Personal communication. University of Chicago, Quadrangle Club.Google Scholar
Ziliak, S.T. (2008). Guinnessometrics: the economic foundation of Student's’ t. Journal of Economic Perspectives, 22, 199–216.CrossRefGoogle Scholar
Ziliak, S.T. (2010). The validus medicus and a new gold standard. The Lancet, 376, 324–325.CrossRefGoogle Scholar
Ziliak, S.T. (2011a). Field experiments in economics: comment on an article by Levitt and List. CREATES Research Paper No. 2011–25, Aarhus: Center for Research in Econometric Analysis of Times Series, Aarhus University, Denmark.Google Scholar
Ziliak, S.T. (2011b). Matrixx v. Siracusano and Student v. Fisher: statistical significance on trial. Significance, 8, 131–134.CrossRefGoogle Scholar
Ziliak, S.T. and McCloskey, D.N. (2008). The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives. Ann Arbor: University of Michigan Press.Google Scholar