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Nonparametric statistical inference / Jean Dickinson Gibbons (University of Alabama (Emerita), Tuscaloosa, U.S.A.), Subhabrata Chakraborti (University of Alabama, Tuscaloosa, U.S.A.)

Von: Mitwirkende(r): Resource type: Ressourcentyp: BuchBuchSprache: Englisch Reihen: A Chapman & Hall book | StatisticsVerlag: Boca Raton ; London ; New York : CRC Press, Taylor & Francis Group, 2021Auflage: Sixth editionBeschreibung: xix, 674 Seiten : Illustrationen, DiagrammeISBN:
  • 9781138087446
  • 9781315110479
Schlagwörter: Andere physische Formen: 9781351616171. | 9781351616164. | Erscheint auch als: Nonparametric Statistical Inference. Online-Ausgabe 6th ed. Milton : CRC Press LLC, 2020. 1 online resource (0 pages)DDC-Klassifikation:
  • 519.5/4
RVK: RVK: SK 850 | SK 830 | QH 233LOC-Klassifikation:
  • QA278.8
Zusammenfassung: "Nonparametric Statistical Inference, Sixth Edition has been thoroughly revised and rewritten to make it more readable and reader-friendly. All of the R solutions are new and make this book much more useful for applications in the modern times. It has been updated throughout and contains 100 new citations, including some of the most recent, to make it more current and useful for researchers. · Covers the most commonly used nonparametric procedures. · States the assumptions, develops the theory behind the procedures, and illustrates the techniques using realistic examples from the social, behavioral, and life sciences. · Presents tests of hypotheses, confidence interval estimation, sample size determination, power, and comparisons of competing procedures. · Includes an Appendix of user-friendly tables needed for solutions to all data- oriented examples. · Gives examples of computer applications based on R, MINITAB, STATXACT, and SAS. Lists over 100 new references"--PPN: PPN: 1726803945
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