Applied nonparametric statistical methods /

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Bibliographic Details
Author / Creator:Sprent, Peter
Edition:2nd ed.
Imprint:London ; New York : Chapman & Hall, 1993.
Description:x, 342 p. : ill. ; 24 cm.
Language:English
Subject:
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/1472322
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ISBN:0412449803 (alk. paper)
Notes:Includes bibliographical references (p. [324]-334) and index.
Table of Contents:
  • 1. Introducing nonparametric methods. 1.1. Basic statistics. 1.2. Samples and populations. 1.3. Hypothesis tests. 1.4. Estimation. 1.5. Computers and nonparametric methods
  • 2. Location tests for single samples. 2.1. Counts and ranks. 2.2. Inferences about medians based on ranks. 2.3. Other location estimators. 2.4. Fields of application
  • 3. Rank transformations and other tests for single samples. 3.1. Using full information. 3.2. Transformation of ranks. 3.3. Matching samples to distributions. 3.4. Practical implications of efficiency. 3.5. Modified assumptions. 3.6. A runs test for randomness. 3.7. Fields of application
  • 4. Methods for paired samples. 4.1. Comparisons in pairs. 4.2. A less obvious use of the sign test. 4.3. Fields of application
  • 5. Methods for two independent samples. 5.1. Location tests and estimates. 5.2. Tests based on transformations of ranks. 5.3. Tests for equality of variance. 5.4. Tests for a common distribution. 5.5. Fields of application
  • 6. Three or more samples. 6.1. Comparisons with parametric methods. 6.2. Location tests for independent samples. 6.3. Location comparisons for related samples. 6.4. More detailed treatment comparisons. 6.5. Tests for heterogeneity of variance. 6.6. Fields of application
  • 7. Correlation and concordance. 7.1. Correlation and bivariate data. 7.2. Ranked data for several variables. 7.3. Fields of application
  • 8. Regression. 8.1. Bivariate linear regression. 8.2. Monotonic regression. 8.3. Multivariate data. 8.4. Fields of application
  • 9. Categorical data. 9.1. Categories and counts. 9.2. Independence with nominal attribute categories. 9.3. Ordered categorical data. 9.4. Goodness-of-fit tests for discrete data. 9.5. Extensions of McNemar's test. 9.6. Fields of application
  • 10. Association in categorical data. 10.1. The analysis of association. 10.2. Some models for contingency tables. 10.3. Analysis of k 2x2 tables. 10.4. Fields of application
  • 11. Robustness. 11.1. The computer and robustness. 11.2. The jackknife. 11.3. The bootstrap. 11.4. Fields of application
  • 12. Other developments. 12.1. Other concepts and methods. 12.2. Further widely used procedures. 12.3. More sophisticated developments. 12.4. The Bayesian approach. 12.5. Choosing a model. App. A1 Random variables
  • App. A2 Permutations and combinations
  • App. A3 Selecting a random sample of r items from n
  • App. A4 The t-distribution and t-tests
  • App. A5 The chi-squared and F-distributions
  • App. A6 Least squares regression
  • App. A7 Badenscallie data set
  • Tables for nonparametric tests.