Overview

Ordinal Data: Nonparametric Statistical Analyses and SPSS Applications familiarizes students with the statistical analysis of ordinal data, commonly utilized in the fields of health, wellness, and behavioral sciences. The book offers foundational knowledge required for understanding and handling data types such as Likert-like scales, ordinal rankings, and nonparametric datasets. It is designed for learners who have a basic understanding of statistics, covering concepts such as hypothesis testing, p-values, and sampling. The text delineates the principles of nonparametric tests and distribution-free methods, as well as detailed procedures for conducting specific tests like the Rank Sum Test and the Signed Rank Test. It discusses the computation of various statistical measures and the interpretation of results, emphasizing that outcomes of analyses should support, but not definitively prove, research hypotheses. The content is structured to provide clarity on methods to analyze data from smaller and larger sample sizes, correct for biases such as ties in data, and report findings according to APA standards. Ordinal Data is ideal for undergraduate or graduate courses focused on nonparametric statistics, quantitative analysis, as well as research methods in the health and behavioral sciences.

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Clifton W. Hamilton is an adjunct professor of anesthesiology, as well as curriculum and instruction, at Barry University. He holds an M.S. in reading from Barry University and an Ed.D. in higher education from Florida International University, where his interest and research in inferential statistics began. That interest led to the completion and presentation of several action research studies designed to improve decision-making for leaders in education and City of North Miami. Prior to teaching in higher education, Dr. Hamilton worked as a middle school teacher teaching language arts, reading, writing, and the visual arts.

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