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Sequential Design of Experiments

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Breakthroughs in Statistics

Part of the book series: Springer Series in Statistics ((PSS))

Abstract

Considerable scientific research is characterized as follows. The scientist is interested in studying a phenomenon. At first he is quite ignorant and his initial experiments are preliminary and tentative. As he gathers relevant data, he becomes more definite in his impression of the underlying theory. This more definite impression is used to construct more informative experiments. Finally after a certain point he is satisfied that his evidence is sufficient to allow him to announce certain conclusions and he does so.

This work was sponsored by the Office of Naval Research under Contract N6 onr-25140 (NR-342-022)

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References

  1. R.N. Bradt, S.M. Johnson, and S. Karlin. “On sequential designs for maximizing the sum of n observations,” Ann. Math. Stat, Vol. 27 (1956), pp. 1060–1074.

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  2. Herman Chernoff, “Large-sample theory; parametric case,” Ann. Math. Stat., Vol. 27 (1956), pp. 1–22.

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  3. J.L. Doob, Stochastic Processes. John Wiley and Sons, Inc., New York, 1953.

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  4. S. Kullback and R.A. Leibler, “On information and sufficiency.” Ann. Math. Stat., Vol. 22 (1951), pp. 79–86.

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  5. H.E. Robbins. “Some aspects of the sequential design of experiments,” Bull. Amer. Math. Soc. Vol. 58, No. 5 (1952), pp. 527 - 535.

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  6. Abraham Wald, Sequential Analysis, John Wiley and Sons, Inc., New York. 1947.

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Author information

Authors and Affiliations

  1. Stanford University, USA

    Herman Chernoff

Authors
  1. Herman Chernoff
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Editor information

Editors and Affiliations

  1. College of Business and Management, University of Maryland at College Park, 20742, College Park, MD, USA

    Samuel Kotz

  2. Department of Statistics Phillips Hall, The University of North Carolina at Chapel Hill, 27599, Chapel Hill, NC, USA

    Norman L. Johnson

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© 1992 Springer-Verlag New York, Inc.

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Chernoff, H. (1992). Sequential Design of Experiments. In: Kotz, S., Johnson, N.L. (eds) Breakthroughs in Statistics. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4380-9_27

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  • DOI: https://doi.org/10.1007/978-1-4612-4380-9_27

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94039-7

  • Online ISBN: 978-1-4612-4380-9

  • eBook Packages: Springer Book Archive

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