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Selecting the highest probability in binomial or multinomial trials.

B Levin1, H Robbins

  • 1Division of Biostatistics, Columbia University School of Public Health and the G. Sergievsky Center, New York, New York 10032.

Proceedings of the National Academy of Sciences of the United States of America
|August 1, 1981
PubMed
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This study evaluates sequential procedures for selecting the best binomial or multinomial population. Procedures with and without elimination were compared based on expected selection probability.

Area of Science:

  • Statistics
  • Probability Theory
  • Statistical Inference

Background:

  • Selecting the best population is a common statistical problem.
  • Sequential procedures offer adaptive sampling strategies.
  • Elimination rules can potentially improve efficiency.

Purpose of the Study:

  • To evaluate sequential procedures for selecting the binomial population with the highest success probability.
  • To assess sequential procedures for selecting the multinomial outcome with the highest cell probability.
  • To compare the performance of procedures with and without sequential elimination.

Main Methods:

  • Consideration of sequential sampling designs.
  • Development of selection rules for binomial and multinomial data.

Related Experiment Videos

  • Analysis of expected probability of correct selection for different procedures.
  • Evaluation of procedures incorporating sequential elimination of inferior populations.

    • Main Results:

    • Performance metrics were established for sequential selection procedures.
    • Comparison of selection probabilities for procedures with and without elimination.
    • Identification of conditions where elimination strategies are advantageous.

    Conclusions:

    • Sequential procedures provide a framework for efficient population selection.
    • The inclusion of elimination rules can enhance the probability of selecting the superior population.
    • The choice of procedure depends on specific statistical and practical considerations.