http://worldcat.org/entity/work/id/793199233

Nonparametric statistics for non-statisticians a step-by-step approach

BA practical and understandable approach to nonparametric statistics for researchers across diverse areas of study/b 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. iNonparametric Statistics for Non-Statisticians: A Step-by-Step Approach/i fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences. Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to:ullidivTest data for normality and randomness/divlidivUse the Wilcoxon signed rank test to compare two related samples/divlidivApply the Mann-Whitney U test to compare two unrelated samples/divlidivCompare more than two related samples using the Friedman test/divlidivEmploy the Kruskal-Wallis iH/i test to compare more than two unrelated samples/divlidivCompare variables of ordinal or dichotomous scales/divlidivTest for nominal scale data/div/ul A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS, and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice. Extensively classroom tested, iNonparametric Statistics for Non-Statisticians/i is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.

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