M. Kraska-Miller

Nonparametric Statistics for Social and Behavioral Sciences (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Incorporating a hands-on pedagogical approach, this text 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. The text is the only current nonparametric book written specifically for students in the behavioral and social sciences. With examples of real-life research problems, it emphasizes sound research designs, appropriate statistical analyses, and accurate interpretations of results.

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Produktdetails

• Verlag: Taylor & Francis
• Erscheinungstermin: 9. Dezember 2013
• Englisch
• ISBN-13: 9781040059562
• Artikelnr.: 72286952

Autorenporträt

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.

Inhaltsangabe

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.