Statistical Science

A Conversation with James O. Berger

Robert L. Wolpert

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James O. Berger was born on April 6, 1950, in Minneapolis, Minnesota, to Orvis and Thelma Berger. He earned his AB, MA and Ph.D. degrees in mathematics from Cornell University in 1971, 1973 and 1974, respectively. He served at Purdue University 1974–1997, as the Richard M. Brumfield Distinguished Professor of Statistics 1986–1997, and at Duke University as the Arts and Sciences Professor of Statistics in the Institute of Statistics and Decision Sciences (ISDS) from 1997 to the present. He is also the Director of the Statistical and Applied Mathematical Sciences Institute (SAMSI), one of the U.S. National Science Foundation’s national institutes in the mathematical and statistical sciences.

Berger served as President of the Institute of Mathematical Statistics (IMS) 1995–1996 and Chair of the Section on Bayesian Statistical Science (SBSS) of the American Statistical Association (ASA) in 1995; he is President of the International Society for Bayesian Analysis (ISBA) in 2004. He has served as Co-Editor of The Annals of Statistics and on the editorial boards of the Springer Series in Statistics, of the Journal of Statistical Planning and Inference, of Statistics and Decisions, of the International Statistical Review and of Test. He has organized or been on the organizing committees of twenty-eight conferences, including five of the Purdue Symposia on Statistical Decision Theory and Related Topics and four of the Valencia International Meetings on Bayesian Statistics.

Berger is the recipient of a host of honors. He is an elected fellow of the AAAS, the ASA and the IMS and an Elected Member of the International Statistical Institute (ISI). He has earned Guggenheim and Sloan Fellowships and was the 1985 winner of the COPSS Presidents’ Award ( joint from IMS, ASA, ENAR, WNAR and CSS) given to an outstanding statistician below forty years of age (it is particularly noteworthy that he won that award at the tender age of 35), and was selected as the COPSS Fisher Lecturer in 2001. He was elected as a foreign member of the Spanish Real Academia de Ciencias in 2002, and to membership in the U.S. National Academy of Sciences in 2003.

Berger has been the advisor of 30 Ph.D. students, has written or edited thirteen books and has numerous other statistical publications. A listing of these publications can be found at his Web site,

Berger married Ann Louise Duer (whom he first met when they were in the seventh grade together) in 1970, and they have two children, Jill Berger, who is married to Sascha Hallstein and works as an optical scientist in Silicon Valley, and Julie Gish, who is married to Ryan Gish and works as a consultant in Chicago.

Article information

Statist. Sci. Volume 19, Number 1 (2004), 205-218.

First available: 14 July 2004

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Wolpert, Robert L. A Conversation with James O. Berger. Statistical Science 19 (2004), no. 1, 205--218. doi:10.1214/088342304000000053.

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  • Bayarri, M. J. and Berger, J. O. (1999). Quantifying surprise in the data and model verification. In Bayesian Statistics 6 (J. M. Bernardo, J. O. Berger, A. P. Dawid and A. F. M. Smith, eds.) 53--82. Oxford Univ. Press.
  • Bayarri, M. J. and Berger, J. O. (2004). The interplay of Bayesian and frequentist analysis. Statist. Sci. 19 58--80.
  • Berger, J. O. (1980). Statistical Decision Theory: Foundations, Concepts and Methods. Springer, New York.
  • Berger, J. O. (2003). Could Fisher, Jeffreys and Neyman have agreed on testing (with discussion)? Statist. Sci. 18 1--32.
  • Berger, J. O., Boukai, B. and Wang, Y. (1997). Unified frequentist and Bayesian testing of a precise hypothesis (with discussion). Statist. Sci. 12 133--160.
  • Berger, J. O., Boukai, B. and Wang, Y. (1999). Simultaneous Bayesian--frequentist sequential testing of nested hypotheses. Biometrika 86 79--92.
  • Berger, J. O., Brown, L. D. and Wolpert, R. L. (1994). A unified conditional frequentist and Bayesian test for fixed and sequential simple hypothesis testing. Ann. Statist. 22 1787--1807.
  • Berger, J. O. and Sellke, T. (1987). Testing a point null hypothesis: The irreconcilability of $P$ values and evidence (with discussion). J. Amer. Statist. Assoc. 82 112--133, 135--139.
  • Berger, J. O. and Wolpert, R. L. (1984). The Likelihood Principle: A Review, Generalizations, and Statistical Implications. IMS, Hayward, CA. (With discussion.)
  • Berger, J. O. and Wolpert, R. L. (1988). The Likelihood Principle: A Review, Generalizations, and Statistical Implications, 2nd ed. IMS, Hayward, CA. (With discussion.)
  • Birnbaum, A. (1962). On the foundations of statistical inference (with discussion). J. Amer. Statist. Assoc. 57 269--326.
  • Chung, K. L. (1968). A Course in Probability Theory. Harcourt, Brace and World, New York. (Second and third editions published 1974 and 2001, Academic Press.)
  • Dass, S. C. and Berger, J. O. (2003). Unified conditional frequentist and Bayesian testing of composite hypotheses. Scand. J. Statist. 30 193--210.
  • Hwang, J. T. and Casella, G. (1982). Minimax confidence sets for the mean of a multivariate normal distribution. Ann. Statist. 10 868--881.
  • Robins, J. M., van der Vaart, A. and Ventura, V. (2000). Asymptotic distribution of $p$-values in composite null models. J. Amer. Statist. Assoc. 95 1143--1156.