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Selecting and ordering populations : [electronic resource] a new statistical methodology / Jean Dickinson Gibbons, Ingram Olkin, Milton Sobel.

By: Contributor(s): Material type: TextTextSeries: Wiley series in probability and mathematical statistics | A Wiley publication in applied statisticsPublication details: New York : Wiley, c1977.Description: xxi, 569 p. : ill. ; 24 cmISBN:
  • 0471026700
  • 9780471026709
Subject(s): Genre/Form: DDC classification:
  • 519.5/4 19
LOC classification:
  • QA278.7 .G5
Other classification:
  • 31.73
  • MS 4100
  • MS 4250
  • QH 233
  • QH 252
  • SK 830
Online resources:
Contents:
1. The philosophy of selecting and ordering populations -- 2. Selecting the one best population for normal distributions with common known variance -- 3. Selecting the one best population for other normal distribution models -- 4. Selecting the one best population for binomial (or Bernoulli) distributions -- 5. Selecting the one normal population with the smallest variance -- 6. Selecting the one best category for the multinomial distribution -- 7. Nonparametric selection procedures -- 8. Selection procedures for a design with paired comparisons -- 9. Selecting the normal population with the best regression value -- 10. Selecting normal populations better than a control -- 11. Selecting the t best out of k populations -- 12. Complete ordering of k populations -- 13. Subset selection (or elimination) procedures -- 14. Selecting the best gamma population -- 15. Selection procedures for multivariate normal distributions.
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Bibliography: p. 543-556.

Includes indexes.

1. The philosophy of selecting and ordering populations -- 2. Selecting the one best population for normal distributions with common known variance -- 3. Selecting the one best population for other normal distribution models -- 4. Selecting the one best population for binomial (or Bernoulli) distributions -- 5. Selecting the one normal population with the smallest variance -- 6. Selecting the one best category for the multinomial distribution -- 7. Nonparametric selection procedures -- 8. Selection procedures for a design with paired comparisons -- 9. Selecting the normal population with the best regression value -- 10. Selecting normal populations better than a control -- 11. Selecting the t best out of k populations -- 12. Complete ordering of k populations -- 13. Subset selection (or elimination) procedures -- 14. Selecting the best gamma population -- 15. Selection procedures for multivariate normal distributions.

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