Nonparametric Statistics for Social and Behavioral Sciences (Hardback) book cover

Nonparametric Statistics for Social and Behavioral Sciences

By M. Kraska-MIller

© 2013 – Chapman and Hall/CRC

260 pages | 138 B/W Illus.

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pub: 2013-12-09
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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

Basic Principles of Research

Planning for Research

Types of Research Designs

Sampling Procedures

Validity and Reliability of Measurement Instruments

Steps of the Research Process

Introduction to Nonparametric Statistics

Data Analysis

Overview of Nonparametric Statistics and Parametric Statistics

Overview of Parametric Statistics

Overview of Nonparametric Statistics

Importance of Nonparametric Methods

Measurement Instruments

Analysis of Data to Determine Association and Agreement

Pearson Chi-Square Test of Association and Independence

Contingency Coefficient

Phi Coefficient and Cramėr's V Coefficient

Kendall’s Taub and Tauc

Kappa Statistic

Spearman Rank-Order Correlation Coefficient

Analyses for Two Independent Samples

Fisher's Exact Test for 2 x 2 Tables

Median Test

Wilcoxon-Mann-Whitney U Test

Kolmogorov-Smirnov Two-Sample Test

Hodges-Lehman Estimate for Confidence Interval

Moses Extreme Reaction Test

Analysis of Multiple Independent Samples

Kruskal-Wallis One-Way Analysis of Variance by Ranks Test

Extended Median Test

Jonckheere-Terpstra Test with Ordered Alternatives

Analysis of Two Dependent Samples

McNemar Change Test

Sign Test for Two Related Samples

Wilcoxon Signed Rank Test

Hodges-Lehman Estimate for Confidence Interval

Tests for Multiple Related Samples

Cochran Q Test

Friedman Analysis of Variance by Ranks Test

Kendall’s Coefficient of Concordance (W)

Analysis of Single Samples

Binomial Test

One-Sample Sign Test

One-Sample Runs Test for Randomness

Pearson Chi-Square Test for Goodness-of-Fit

Kolmogorov-Smirnov One-Sample Test


A Summary, Exercises, and References appear at the end of each chapter.

About the Author

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.

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General