A Brief History of the Statistics Department of the University of California at Berkeley

Abstract

The early history of our department was dominated by Jerzy Neyman (1894–1981), while the next phase was largely in the hands of Neyman’s students, with Erich Lehmann (1917–2009) being a central, long-lived, and much loved member of this group. We are very fortunate in having the biography Neyman—From Life written by Constance Reid (1918–2010), and Erich’s Reminiscences of a Statistician: The Company I Kept and other historical material documenting the founding and growth of the department, and the people in it. In what follows we will draw heavily on these sources, describing what seems to us a remarkable success story: one person starting “a cell of statistical research and teaching not being hampered by any existing traditions and routines,” and seeing that cell grow rapidly into a major force in academic statistics worldwide. That it has remained so since its founding is a testament to the strength of Neyman’s model for a department of statistics.

Appendix

1. Books by Neyman and the Founders

• For brevity we give first editions only. Many of these books have multiple editions, and translations into other languages. Also, we omit edited volumes, such as the Proceedings of the Berkeley Symposia on Probability and Mathematical Statistics, which are all readily available in PROJECT euclid.

• David Blackwell and M. A. Girshick. (1954). Theory of games and statistical decisions. John Wiley and Sons, Inc., New York, xi + 355.

• David Blackwell. (1970). Basic Statistics. McGraw-Hill, New York.

• J. L. Hodges and Richard S. Crutchfield and David Krech. (1993). StatLab : an Empirical Introduction to Statistics. McGraw-Hill Ryerson, Limited, 376.

• J. L. Hodges, Jr. and E. L. Lehmann. (1965). Elements of finite probability. Holden-Day Inc., San Francisco, Calif., vi + 230.

• J. L. Hodges, Jr. and E. L. Lehmann. (1964). Basic concepts of probability and statistics. Holden-Day Inc. San Francisco, Calif., xiii + 375.

• Lucien Le Cam. (1986). Asymptotic methods in statistical decision theory. Springer-Verlag, New York, xxvi + 742.

• Lucien Le Cam and Grace Lo Yang. (1990). Asymptotics in statistics. Some basic concepts Springer-Verlag, New York, viii + 180.

• E. L. Lehmann. (1959). Testing statistical hypotheses. John Wiley & Sons Inc., New York, xiii + 369.

• E. L. Lehmann. (1975). Nonparametrics: statistical methods based on ranks. With the special assistance of H. J. M. d’Abrera, Holden-Day Series in Probability and Statistics Holden-Day Inc., San Francisco, Calif., xvi + 457.

• Erich Leo Lehmann. (1983). Theory of point estimation. A Wiley Publication in Mathematical Statistics John Wiley & Sons Inc., New York, xii + 506.

• E. L. Lehmann. (2008). Reminiscences of a statistician: The company I kept. Springer, New York, xii + 309.

• E. L. Lehmann (2011). Fisher, Neyman, and the Creation of Classical Statistics. New York: Springer-Verlag.

• Michel Loève. (1955). Probability theory. Foundations. Random sequences. D. Van Nostrand Company, Inc., Toronto-New York–London, xv + 515.

• J. Neyman (1938). Lectures and Conferences on mathematical statistics. Graduate School, US Department of Agriculture. Washington D.C. 1938. 160.

• J. Neyman. (1950). First Course in Probability and Statistics. Henry Holt and Co., New York, N. Y., ix + 350.

• J. Neyman. (1967). A selection of early statistical papers of J. Neyman. University of California Press, ix + 429.

• J. Neyman and E. S. Pearson. (1967). Joint statistical papers of J. Neyman and E. S. Pearson. University of California Press, iv + 299.

• Henry Scheffé. (1959). The analysis of variance. John Wiley & Sons Inc., New York, xvi + 477.

• Charles Stein. (1986). Approximate computation of expectations. Institute of Mathematical Statistics, Hayward, CA, iv + 164.

2. Selected Books by Non-founders

• The books below are representative of a much larger number written by faculty in Berkeley Statistics. Again, we restrict to first editions only, and omit reference to translations, conference proceedings, or collections of other kinds.

• David J. Aldous. (1985). Exchangeability and related topics. École d’Été de probabilites de Saint-Flour, XIII, 1–198, Lecture Notes in Math., 1117. Springer, Berlin, 1–198.

• Martin Anthony and Peter Bartlett (1999) Neural Network Learning: Theoretical foundations. Cambridge University Press. xiv + 389.

• Peter J Bickel and Kjell A. Doksum. (1976). Mathematical statistics. Basic ideas and selected topics, Holden-Day Series in Probability and Statistics Holden-Day Inc., San Francisco, Calif., xiv + 493.

• Leo Breiman, Jerome H. Friedman, Richard A. Olshen, and Charles J. Stone. (1983) Classification and Regression Trees. Wadsworth Advanced Books and Software, Belmont, CA.

• David R. Brillinger. (1975). Time series. Data analysis and theory, International Series in Decision Processes Holt, Rinehart and Winston, Inc., New York, xii + 500.

• Ching-Shui Cheng (2013) Theory of Factorial Design. Chapman and Hall.

• Lester E. Dubins and L. Jimmy Savage (1965) How to Gamble if You Must: Inequalities for stochastic processes. McGraw-Hill Book Co., New York-Toronto-London-Sydney. xiv + 249.

• Steven N. Evans. (2008). Probability and real trees. Lectures from the 35th Summer School on Probability Theory held in Saint-Flour, July 6–23, 2005 Springer, Berlin, xii + 193.

• David A. Freedman. (2005). Statistical models: theory and practice. Cambridge University Press, Cambridge. x + 414.

• David A. Freedman. (2010). Statistical models and causal inference. A dialogue with the social sciences, Edited by David Collier, Jasjeet S. Sekhon and Philip B. Stark Cambridge University Press, Cambridge, xvi + 399.

• David Freedman and Robert Pisani and Roger Purves (1978). Statistics. W. W. Norton & Co.

• Deborah Nolan and Terry Speed (2000) Stat Labs: Mathematical Statistics through Applications, Springer. xviii + 300.

• Jim Pitman. (2006). Combinatorial stochastic processes. Lectures from the 32nd Summer School on Probability Theory held in Saint-Flour, July 7–24, 2002. Springer-Verlag, Berlin, x + 256.

• Jim Pitman. (1993). Probability. Springer, xi + 559.

• John A. Rice. (2006). Mathematical statistics and data analysis. Cengage Learning, 666.

• P. B. Stark (1997). SticiGui: Statistics Tools for Internet and Classroom Instruction with a Graphical User Interface. http://statistics.berkeley.edu/~stark/SticiGui

• Charles Stone (1995) A Course in Probability and Statistics. Duxbury, 838.

• Aram J. Thomasian. (1969). The structure of probability theory with applications. McGraw-Hill, 746.

• Martin J. Wainwright and Michael I. Jordan (2008). Graphical Models, Exponential Families, and Variational Inference. Foundations and Trends in Machine Learning. Vol. 1: No 1–2, pp 1–305.

3. Photographs

See Figs. 1, 2, and 3. For more photos, including L. Le Cam, M Loève, H. Scheffé and E Barankin, and others, please go to http://www.stat.berkeley.edu/photos

Fig. 1

From left to right. 1. E. L. Crow. 2. E. S. Keeping. 3. V. Lenzen. 4. D. G. Chapman. 5. C. Stein 6. E. Crow. 7. E. Fix. 8. S. W. Nash. 9. E. L. Scott. 10. D. Cruden Lowry. 11. J. Gurland. 12. I. Elvebach. 13. E. L. Lehmann 14. T. A. Jeeves. 15. E. Seiden. 16. E. A. Fay. 17. B. Epstein. 18. R. T. Birge. 19. I. Blumen. 20. Unknown. 21. B. M. Bennett. 22. J. L. Hodges, Jr. 23. T. Hodges. 24. H. Cramér. 25. G. R. Seth. 26. J. Neyman. 27. H. Hotelling. 28. Z. Szatrowski. (Stat. Lab. Univ. of Calif. Summer Session 1947)

Fig. 2

From left to right. F. N. David, E. L. Scott, D. Blackwell and E. Fix. (Photo taken about 1960)

Fig. 3

From left to right. Front row: Deb Nolan, Philip Stark, Peter Bickel, Elizabeth Purdom, Roger Purves, Julie Shaffer, Martin Wainwright, Michael Klass. Middle row: Ani Adhikari, Cari Kaufman, Haiyan Huang, Jim Pitman, Chuck Stone, Jon McAuliffe, Sandrine Dudoit, Bin Yu, Michael Jordan. Back row: Jas Sekhon, Aditya Guntuboyina, Allan Sly, Peter Bartlett, Nick Jewell, Steve Evans, Elchanan Mossel, Terry Speed. (Faculty in February 2012)