Statistical Science

A Report on the Future of Statistics

Bruce G. Lindsay, Jon Kettenring, and David O. Siegmund

Full-text: Open access


In May 2002 a workshop was held at the National Science Foundation to discuss the future challenges and opportunities for the statistics community. After the workshop the scientific committee produced an extensive report that described the general consensus of the community. This article is an abridgment of the full report.

Article information

Statist. Sci., Volume 19, Number 3 (2004), 387-413.

First available in Project Euclid: 16 March 2005

Permanent link to this document

Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Research funding National Science Foundation challenges opportunities statistical education


Lindsay, Bruce G.; Kettenring, Jon; Siegmund, David O. A Report on the Future of Statistics. Statist. Sci. 19 (2004), no. 3, 387--413. doi:10.1214/088342304000000404.

Export citation


  • Breiman, L. (2001). Statistical modeling: The two cultures (with discussion). Statist. Sci. 16 199--231.
  • Efron, B. (1979). Bootstrap methods: Another look at the jackknife. Ann. Statist. 7 1--26.
  • Feldman, G. J. and Cousins, R. D. (1998). Unified approach to the classical statistical analysis of small signals. Phys. Rev. D 57 3873--3889.
  • Hall, P. and Titterington, D. M. (1987). Common structure of techniques for choosing smoothing parameters in regression problems. J. Roy. Statist. Soc. Ser. B 49 184--198.
  • Miller, C. J., Nichol, R. C. and Batuski, D. J. (2001). Acoustic oscillations in the early universe and today. Science 292 2302--2303.
  • Miller, C. J. et al. (2001). Controlling the false-discovery rate in astrophysical data analysis. Astronomical J. 122 3492--3505.
  • National Research Council (1996). Statistical Software Engineering. National Academies Press, Washington.
  • National Science Foundation (1998). Report of the senior assessment panel of the international assessment of the U.S. mathematical science. Report 98-95, National Science Foundation, Arlington, VA.
  • Raftery, A. E., Tanner, M. A. and Wells, M. T., eds. (2002). Statistics in the 21st Century. Chapman and Hall/CRC Press, London.
  • Simes, R. J. (1986). An improved Bonferroni procedure for multiple tests of significance. Biometrika 73 751--754.
  • Stenseth, N. C., Falck, W., Bjørnstad, O. N. and Krebs, C. J. (1997). Population regulation in snowshoe hare and Canadian lynx: Asymmetric food web configurations between hare and lynx. Proc. Natl. Acad. Sci. USA 94 5147--5152.
  • Stenseth, N. C. et al. (1998). From patterns to processes: Phase and density dependencies in the Canadian lynx cycle. Proc. Natl. Acad. Sci. USA 95 15430--15435.
  • Stenseth, N. C. et al. (2004a). Snow conditions may create an invisible barrier for lynx. Proc. Natl. Acad. Sci. USA 101 10632--10634.
  • Stenseth, N. C. et al. (2004b). The effect of climatic forcing on population synchrony and genetic structuring of the Canadian lynx. Proc. Natl. Acad. Sci. USA 101 6056--6061.
  • Wegman, E. J. (1995). Huge data sets and the frontiers of computational feasibility. J. Comput. Graph. Statist. 4 281--295.