http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Nonparametric statistics for non-statisticians
1 online resource (xiii, 247 pages) : illustrations
A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for.
Front Matter -- Nonparametric Statistics: An Introduction -- Testing Data for Normality -- Comparing Two Related Samples: The Wilcoxon Signed Ranks Test -- Comparing Two Unrelated Samples: The Mann₆Whitney U-Test -- Comparing More Than Two Related Samples: The Friedman Test -- Comparing More than Two Unrelated Samples: The Kruskal₆Wallis H-Test -- Comparing Variables of Ordinal or Dichotomous Scales: Spearman Rank-Order, Point-Biserial, and Biserial Correlations -- Tests for Nominal Scale Data: Chi-Square and Fisher Exact Test -- Test For Randomness: The Runs Test -- Appendix A: SPSS at a Glance -- Appendix B: Tables of Critical Values -- Bibliography -- Index.
Testing data for normality -- Comparing two related samples : the Wilcoxon signed ranks test -- Comparing two unrelated samples : the Mann-Whitney U-test -- Comparing more than two related samples : the Friedman test -- Comparing more than two unrelated samples : the Kruskal-Wallis H test -- Comparing variables of ordinal or dichotomous scales : Spearman rank-order, point-biserial, and biserial correlations -- Tests for nominal scale data : chi-square and Fisher exact test -- Test for randomness : the runs test.
Includes bibliographical references (pages 243-244) and index.