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

By: Gibbons, Jean Dickinson, 1938-.
Contributor(s): Olkin, Ingram [joint author.] | Sobel, Milton, 1919- [joint author.].
Material type: TextTextSeries: Wiley series in probability and mathematical statistics ; A Wiley publication in applied statistics. Publisher: New York : Wiley, c1977Description: xxi, 569 p. : ill. ; 24 cm.ISBN: 0471026700; 9780471026709.Subject(s): Order statistics | Ranking and selection (Statistics) | Statistiques ordonnées | population | méthode statistique | BiostatistikGenre/Form: Populationstheorie.DDC classification: 519.5/4 Other classification: 31.73 | MS 4100 | MS 4250 | QH 233 | QH 252 | SK 830 Online resources: Free eBook from the Internet Archive | Additional information and access via Open Library
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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