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Concepts of Nonparametric Theory

  • Book
  • © 1981

Overview

Authors:
  1. John W. Pratt

    1. Graduate School of Business Administration, Harvard University, Boston, USA

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    You can also search for this author in PubMed   Google Scholar

  2. Jean D. Gibbons

    1. Graduate School of Business Administration, University of Alabama, USA

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    You can also search for this author in PubMed   Google Scholar

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

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Concepts of Statistical Inference and the Binomial Distribution

    • John W. Pratt, Jean D. Gibbons
    Pages 1-81

  3. One-Sample and Paired-Sample Inferences Based on the Binomial Distribution

    • John W. Pratt, Jean D. Gibbons
    Pages 82-144

  4. One-Sample and Paired-Sample Inferences Based on Signed Ranks

    • John W. Pratt, Jean D. Gibbons
    Pages 145-202

  5. One-Sample and Paired-Sample Inferences Based on the Method of Randomization

    • John W. Pratt, Jean D. Gibbons
    Pages 203-230

  6. Two-Sample Rank Procedures for Location

    • John W. Pratt, Jean D. Gibbons
    Pages 231-295

  7. Two-Sample Inferences Based on the Method of Randomization

    • John W. Pratt, Jean D. Gibbons
    Pages 296-317

  8. Kolmogorov-Smirnov Two-Sample Tests

    • John W. Pratt, Jean D. Gibbons
    Pages 318-344

  9. Asymptotic Relative Efficiency

    • John W. Pratt, Jean D. Gibbons
    Pages 345-424

  10. Back Matter

    Pages 425-463
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Keywords

About this book

This book explores both non parametric and general statistical ideas by developing non parametric procedures in simple situations. The major goal is to give the reader a thorough intuitive understanding of the concepts underlying nonparametric procedures and a full appreciation of the properties and operating characteristics of those procedures covered. This book differs from most statistics books by including considerable philosophical and methodological discussion. Special attention is given to discussion of the strengths and weaknesses of various statistical methods and approaches. Difficulties that often arise in applying statistical theory to real data also receive substantial attention. The approach throughout is more conceptual than mathematical. The "Theorem-Proof" format is avoided; generally, properties are "shown," rather than "proved." In most cases the ideas behind the proof of an im­ portant result are discussed intuitively in the text and formal details are left as an exercise for the reader. We feel that the reader will learn more from working such things out than from checking step-by-step a complete presen­ tation of all details.

Authors and Affiliations

  • Graduate School of Business Administration, Harvard University, Boston, USA

    John W. Pratt

  • Graduate School of Business Administration, University of Alabama, USA

    Jean D. Gibbons

Bibliographic Information

  • Book Title: Concepts of Nonparametric Theory

  • Authors: John W. Pratt, Jean D. Gibbons

  • Series Title: Springer Series in Statistics

  • DOI: https://doi.org/10.1007/978-1-4612-5931-2

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Spring-Verlag New York Inc. 1981

  • Softcover ISBN: 978-1-4612-5933-6Published: 10 February 2012

  • eBook ISBN: 978-1-4612-5931-2Published: 06 December 2012

  • Series ISSN: 0172-7397

  • Series E-ISSN: 2197-568X

  • Edition Number: 1

  • Number of Pages: 462

  • Topics: Applications of Mathematics

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