Statistical Science

A Conversation with Martin Bradbury Wilk

Christian Genest and Gordon Brackstone

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Abstract

Martin Bradbury Wilk was born on December 18, 1922, in Montréal, Québec, Canada. He completed a B.Eng. degree in Chemical Engineering in 1945 at McGill University and worked as a Research Engineer on the Atomic Energy Project for the National Research Council of Canada from 1945 to 1950. He then went to Iowa State College, where he completed a M.Sc. and a Ph.D. degree in Statistics in 1953 and 1955, respectively. After a one-year post-doc with John Tukey, he became Assistant Director of the Statistical Techniques Research Group at Princeton University in 1956–1957, and then served as Professor and Director of Research in Statistics at Rutgers University from 1959 to 1963. In parallel, he also had a 14-year career at Bell Laboratories, Murray Hill, New Jersey. From 1956 to 1969, he was in turn Member of Technical Staff, Head of the Statistical Models and Methods Research Department, and Statistical Director in Management Sciences Research. He wrote a number of influential papers in statistical methodology during that period, notably testing procedures for normality (the Shapiro–Wilk statistic) and probability plotting techniques for multivariate data. In 1970, Martin moved into higher management levels of the American Telephone and Telegraph (AT&T) Company. He occupied various positions culminating as Assistant Vice-President and Director of Corporate Planning. In 1980, he returned to Canada and became the first professional statistician to serve as Chief Statistician. His accomplishments at Statistics Canada were numerous and contributed to a resurgence of the institution’s international standing. He played a crucial role in the reinstatement of the Cabinet-cancelled 1986 Census. He remained active after his retirement, serving as a Senior Advisor to the Privy Council Office as well as on several national commissions. In addition, he chaired the Canadian National Task Forces on Tourism Data and on Health Information. Martin is a former President of the Statistical Society of Canada (SSC) and Vice-President of the American Statistical Association (ASA). He is an elected member of the International Statistical Institute and an honorary member of the SSC. He has received many honors, including the George Snedecor Prize, the Jack Youden Prize, the F.G. Brander Memorial Award, the SSC Gold Medal, and a Distinguished Alumni Achievement Citation from Iowa State University. He is a fellow of the Institute of Mathematical Statistics, the American Statistical Association, the Royal Statistical Society, the American Association for the Advancement of Science, and the New York Academy of Science. He was made an Officer of the Order of Canada in 1999 for his “insightful guidance on important matters related to our country’s national statistical system.”

The following conversation took place at Martin Wilk’s home in Salem, Oregon, October 6–7, 2005.

Article information

Source
Statist. Sci. Volume 25, Number 2 (2010), 258-273.

Dates
First available in Project Euclid: 19 November 2010

Permanent link to this document
http://projecteuclid.org/euclid.ss/1290175846

Digital Object Identifier
doi:10.1214/08-STS272

Mathematical Reviews number (MathSciNet)
MR2789994

Citation

Genest, Christian; Brackstone, Gordon. A Conversation with Martin Bradbury Wilk. Statistical Science 25 (2010), no. 2, 258--273. doi:10.1214/08-STS272. http://projecteuclid.org/euclid.ss/1290175846.


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References

  • [1] Fellegi, I. P. and Wilk, M. B. (1988). Is statistics singular or plural? Canad. J. Statist. 16 Supplement, 1–8.
  • [2] Gabbe, J. D., Wilk, M. B. and Brown, W. L. (1967). Statistical analysis and modeling of the high-energy proton data from the Telstar 1 satellite. Bell System Tech. J. 46 1301–1450.
  • [3] Gentleman, J. F. and Wilk, M. B. (1975). Detecting outliers in a two-way table. I. Statistical behavior of residuals. Technometrics 17 1–14.
  • [4] Gentleman, J. F. and Wilk, M. B. (1975). Detecting outliers. II. Supplementing the direct analysis of residuals. Biometrics 31 387–410.
  • [5] Gnanadesikan, R., Kempthorne, O., Nicholson, W. L., Wilk, M. B. and Zelen, M. (1979). Statistical consulting. Transcript of panel discussion. In Proc. of Computer Science and Statistics: 12th Annual Symposium on the Interface 69–95.
  • [6] Gnanadesikan, R. and Wilk, M. B. (1969). Data analytic methods in multivariate statistical analysis. In Multivariate Analysis II (Proc. Second Internat. Sympos., Dayton, Ohio, 1968) 593–638. Academic Press, New York.
  • [7] Gnanadesikan, R. and Wilk, M. B. (1970). Use of maximum likelihood for estimating error variance from a collection of analysis of variance mean squares. Ann. Math. Statist. 41 292–304.
  • [8] Gnanadesikan, R. and Wilk, M. B. (1970). A probability plotting procedure for general analysis of variance. J. Roy. Statist. Soc. Ser. B 32 88–101.
  • [9] Hogben, D., Pinkham, R. S. and Wilk, M. B. (1961). The moments of the non-central t-distribution. Biometrika 48 465–468.
  • [10] Hogben, D., Pinkham, R. S. and Wilk, M. B. (1964). An approximation to the distribution of Q (a variate related to the non-central t). Ann. Math. Statist. 35 315–318.
  • [11] Hogben, D., Pinkham, R. S. and Wilk, M. B. (1964). The moments of a variate related to the non-central t. Ann. Math. Statist. 35 298–314.
  • [12] Lundberg, J. L., Wilk, M. B. and Huyett, M. J. (1960). Solubilities and diffusivities of nitrogen in polyethylene. J. Appl. Phys. 31 1131–1132.
  • [13] Lundberg, J. L., Wilk, M. B. and Huyett, M. J. (1962). Estimation of diffusivities and solubilities from sorption studies. J. Polymer. Sci. 57 275–299.
  • [14] Lundberg, J. L., Wilk, M. B. and Huyett, M. J. (1963). Sorption studies using automation and computation. Ind. Eng. Chem. Fundam. 2 37–43.
  • [15] Pinkham, R. S. and Wilk, M. B. (1963). Tail areas of the t-distribution from a Mills’-ratio-like expansion. Ann. Math. Statist. 34 335–337.
  • [16] Shapiro, S. S. and Wilk, M. B. (1965). An analysis of variance test for normality: Complete samples. Biometrika 52 591–611.
  • [17] Shapiro, S. S. and Wilk, M. B. (1968). Approximations for the null distribution of the W statistic. Technometrics 10 861–866.
  • [18] Shapiro, S. S. and Wilk, M. B. (1972). An analysis of variance test for the exponential distribution (complete samples). Technometrics 14 355–370.
  • [19] Shapiro, S. S., Wilk, M. B. and Chen, H. J. (1968). A comparative study of various tests for normality. J. Amer. Statist. Assoc. 63 1343–1372.
  • [20] Tukey, J. W. and Wilk, M. B. (1965). Data analysis and statistics: Techniques and approaches. In Proc. Cal. Tech. Symposium on Information Processing in Sight Sensory Systems 7–27. Reprinted in The Collected Works of John W. Tukey, Vol. 5, Graphics 1965–1985, pp. 1–22 (1988).
  • [21] Tukey, J. W. and Wilk, M. B. (1966). Data analysis and statistics: An expository overview. AFIPS Conf. Proc. 1966 Fall Joint Comp. Conf. 29 695–709. Reprinted in The Collected Works of John W. Tukey, Vol. 4, Philosophy and Principles of Data Analysis 1965–1986, pp. 549–578 (1988).
  • [22] Tukey, J. W. and Wilk, M. B. (1988). Data analysis and statistics: Principles and practice. In The Collected Works of John W. Tukey 5, Graphics 1965–1985, 23–29.
  • [23] Wilk, M. B. (1949). Preparation and extraction of S35. Canad. J. Res. 27 475–488.
  • [24] Wilk, M. B. (1955). The randomization analysis of a generalized randomized block design. Biometrika 42 70–79.
  • [25] Wilk, M. B. (1956). Linear models in the analysis of variance. In Proc. 2nd Conference on Design of Experiments in Army Research Development and Testing 243–257.
  • [26] Wilk, M. B. (1970). The corporation and the university as social engineers. In Proc. of University of Maryland Seminar on “University, The Corporation and American Priorities in the Seventies.”
  • [27] Wilk, M. B. (1972). Utility prices and allowed rate of return. In Proc. Second Annual Regulatory Information Systems Conference. St. Louis, Missouri.
  • [28] Wilk, M. B. (1973). The study of complex systems. In Computer Science and Statistics: Proceedings of the Seventh Annual Symposium on the Interface (W. J. Kennedy, ed.) 2–10. Iowa State Univ., Ames, Iowa.
  • [29] Wilk, M. B. (1975). Planning and uncertainty. In Proc. Computer Science and Statistics: 8th Annual Symposium on the Interface 510–516. Los Angeles, California.
  • [30] Wilk, M. B. (1975). Uncertainties in analysis of complex systems. In Proceedings of the Symposium on Statistics and Related Topics (A. K. Md. E. Saleh, ed.) 14.01–14.17. Carleton Univ., Ottawa, Ontario, Canada.
  • [31] Wilk, M. B. (1985). The relationship between statisticians and statisticians. Survey Methodology 11 89–94.
  • [32] Wilk, M. B. (1985). Statisticiens et statisticiens. Techniques d’enquête 11 101–107.
  • [33] Wilk, M. B. (1986). Summary of comments at 1986 Annual Meeting of SSC. SSC Newsletter 14(2) 7–11.
  • [34] Wilk, M. B. (1986). A message from the President. / Le billet du président. Liaison 1(1) 8–11.
  • [35] Wilk, M. B. (1987). A message from the President. / Le billet du président. Liaison 1(2) 8–9.
  • [36] Wilk, M. B. (1987). The concept of error in statistical and scientific work. In Proc. Third Annual Research Conf. 223–228. Bureau of the Census, Washington, DC.
  • [37] Wilk, M. B. and Gnanadesikan, R. (1961). Graphical analysis of multi-response experimental data using ordered distances. Proc. Nat. Acad. Sci. USA 47 1209–1212.
  • [38] Wilk, M. B. and Gnanadesikan, R. (1964). Graphical methods for internal comparisons in multi-response experiments. Ann. Math. Statist. 35 613–631.
  • [39] Wilk, M. B. and Gnanadesikan, R. (1968). Probability plotting methods for the analysis of data. Biometrika 55 1–17.
  • [40] Wilk, M. B., Gnanadesikan, R. and Freeny, A. E. (1963). Estimation of error variance from smallest ordered contrasts. J. Amer. Statist. Assoc. 58 152–160.
  • [41] Wilk, M. B., Gnanadesikan, R. and Huyett, M. J. (1962). Probability plots for the gamma distribution. Technometrics 4 1–20.
  • [42] Wilk, M. B., Gnanadesikan, R. and Huyett, M. J. (1962). Estimation of parameters of the gamma distribution using order statistics. Biometrika 49 525–545.
  • [43] Wilk, M. B., Gnanadesikan, R. and Huyett, M. J. (1963). Separate maximum likelihood estimation of scale or shape parameters of the gamma distribution using order statistics. Biometrika 50 217–221.
  • [44] Wilk, M. B., Gnanadesikan, R. and Lauh, E. (1966). Scale parameter estimation from the order statistics of unequal gamma components. Ann. Math. Statist. 37 152–176.
  • [45] Wilk, M. B. and Kempthorne, O. (1955). Fixed, mixed, and random models. J. Amer. Statist. Assoc. 50 1144–1167.
  • [46] Wilk, M. B. and Kempthorne, O. (1956). Some aspects of the analysis of factorial experiments in a completely randomized design. Ann. Math. Statist. 27 950–985.
  • [47] Wilk, M. B. and Kempthorne, O. (1957). Non-additivities in a Latin square design. J. Amer. Statist. Assoc. 52 218–236.
  • [48] Wilk, M. B. and Shapiro, S. S. (1968). The joint assessment of normality of several independent samples. Technometrics 10 825–839.
  • [49] Wilk, M. B., Torrey, M. N. and Gohn, G. R. (1958). A study of the variability in the mechanical properties of alloy A phosphor bronze strip. Proc. Amer. Soc. Test. Mater. 58 893–910. (Discussion on pp. 910–911.)