Non-parametric statistics
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Date
2009
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Publisher
Mzumbe University
Abstract
The book is structured as follows: Chapter one introduces the basic concepts of a statistical inference problem. Chapter two focuses on inference techniques that are appropriate for nominal data. Chapters three and four dwell on inference techniques using ordinal data; with chapter three focusing on sample median test techniques and chapter four on rank-sum techniques. Both techniques typically rely on data that are capable of being ranked. Chapter five is exclusively presenting material on testing randomness of a set of sample observations, which is a universal premise for all inference methods. The technique adopted in this book is based on Wald-Wolfowitz one-sample runs test procedure. The final chapter dwells on correlational inference techniques that are appropriate for nominal and/or ordinal data.
The author has streamlined the material to be reader-friendly. The solved examples, exercises, and review questions that are drawn from real and contextualized business, economics, management, and social life situations enable readers to understand the topical concepts covered. The optional exercises on parametric techniques enable readers to reflect on the link between parametric and non-parametric statistical techniques as applied in social science research. Chapters two through six each contain a section on SPSS tutorial, in which the use of SPSS software in solving non- Parametric inference problems is demonstrated. In this way, readers get to know and/or exercise their skills in the application of the statistical package.
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Keywords
Social research inference, measurement scale, Qualitative research, Statistical hypothesis, Non-parametric techniques, Inference techniques, Nominal data inference techniques, Binomial test technique, Ordinal data inference techniques, The sign test, Median test, Rank sum tests, Inference methods correlation
Citation
APA