Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM’s SPSS software.
This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text:
- Explains a conceptual framework for each statistical procedure
- Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure
- Details SPSS paths for conducting various analyses
- Discusses the interpretations of statistical results and conclusions of the research
With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.
Table of Contents
Introduction to Research in Social and Behavioral Sciences. Introduction to Nonparametric Statistics. Analysis of Data to Determine Association and Agreement. Analyses for Two Independent Samples. Analysis of Multiple Independent Samples. Analysis of Two Dependent Samples. Tests for Multiple Related Samples. Analysis of Single Samples. Index.
Dr. M. Kraska-Miller is a Mildred Cheshire Fraley Distinguished Professor of Research and Statistics in the Department of Educational Foundations, Leadership, and Technology at Auburn University, where she is also the Interim Director of Research for the Center for Disability Research and Service. Dr. Kraska-Miller is the author of four books on teaching and communications. She has published numerous articles in national and international refereed journals. Her research interests include statistical modeling and applications of statistics to theoretical concepts, such as motivation; satisfaction in jobs, services, income, and other areas; and needs assessments particularly applicable to special populations. She earned a Ph.D. in technical education, statistics from the University of Missouri; an M.S. in technical education, statistics from the University of Wisconsin-Stout; and an M.S. in probability and statistics from Auburn University.
Datasets for chapter 8.zip
Datasets for chapter 7.zip
Datasets for chapter 6.zip
Datasets for chapter 5.zip
Datasets for chapter 4.zip
Datasets for chapter 3.zip
To gain access to the instructor resources for this title, please visit the Instructor Resources Download Hub.
You will be prompted to fill out a regist