Nonparametric Statistics: A Step-by-Step Approach 2nd Edition

Praise for the First Edition

“… a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory.”

– CHOICE

The Second Edition of Nonparametric Statistics: A Step-by-Step Approach 2nd Edition continues to present nonparametric statistical procedures in an accessible manner for readers with backgrounds in the social, behavioral, biological, and physical sciences. Each chapter presents several nonparametric procedures and context-based examples in a step-by-step fashion. Additionally, SPSS® screen captures are used to demonstrate how to perform and interpret the results from the respective procedures. Finally, the authors cite and briefly describe examples of each nonparametric test from diverse fields. In addition,

Nonparametric Statistics: A Step-by-Step Approach, Second Edition features:

• New coverage of the sign test and the Kolmogorov-Smirnov two-sample test, both of which provide a logical and natural progression to statistical power

• Expanded treatment of basic topics, such as parameters and empirical distribution frequency

• A multitude of practical examples that enhance and expand the statistical toolset for readers

• Tables of critical values and solutions to select problems to aid in reader comprehension

• Supplemental material including online decision trees to better determine the type of statistical test needed as well as narrated videos and screen animations with step-by-step instructions on how to perform the tests using SPSS

Nonparametric Statistics: A Step-by-Step Approach, Second Edition is an excellent textbook for upper-undergraduate and beginning graduate students majoring in the physical, social, behavioral, and health sciences as well as education. The book also serves as a valuable reference for applied statisticians and practitioners working in industry and professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and their relevant applications.

Praise for the First Edition

“… a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory.”

– CHOICE

The Second Edition of Nonparametric Statistics: A Step-by-Step Approach 2nd Edition continues to present nonparametric statistical procedures in an accessible manner for readers with backgrounds in the social, behavioral, biological, and physical sciences. Each chapter presents several nonparametric procedures and context-based examples in a step-by-step fashion. Additionally, SPSS® screen captures are used to demonstrate how to perform and interpret the results from the respective procedures. Finally, the authors cite and briefly describe examples of each nonparametric test from diverse fields. In addition,

Nonparametric Statistics: A Step-by-Step Approach, Second Edition features:

• New coverage of the sign test and the Kolmogorov-Smirnov two-sample test, both of which provide a logical and natural progression to statistical power

• Expanded treatment of basic topics, such as parameters and empirical distribution frequency

• A multitude of practical examples that enhance and expand the statistical toolset for readers

• Tables of critical values and solutions to select problems to aid in reader comprehension

• Supplemental material including online decision trees to better determine the type of statistical test needed as well as narrated videos and screen animations with step-by-step instructions on how to perform the tests using SPSS

Nonparametric Statistics: A Step-by-Step Approach, Second Edition is an excellent textbook for upper-undergraduate and beginning graduate students majoring in the physical, social, behavioral, and health sciences as well as education. The book also serves as a valuable reference for applied statisticians and practitioners working in industry and professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and their relevant applications.