Decision Support Using Nonparametric Statistics

  • Warren Beatty

Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Warren Beatty
    Pages 1-2
  3. Warren Beatty
    Pages 3-3
  4. Warren Beatty
    Pages 5-16
  5. Warren Beatty
    Pages 17-22
  6. Warren Beatty
    Pages 43-54
  7. Warren Beatty
    Pages 55-78
  8. Warren Beatty
    Pages 79-85
  9. Warren Beatty
    Pages 87-96
  10. Back Matter
    Pages 97-115

About this book


This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective. While many degree programs require a course in parametric statistics, these methods are often inadequate for real-world decision making in business environments. Much of the data collected today by business executives (for example, customer satisfaction opinions) requires nonparametric statistics for valid analysis, and this book provides the reader with a set of tools that can be used to validly analyze all data, regardless of type. Through numerous examples and exercises, this book explains why nonparametric statistics will lead to better decisions and how they are used to reach a decision, with a wide array of business applications. Online resources include exercise data, spreadsheets, and solutions.


nonparametric statistics business decision making hypothesis development and testing sampling error margin of error spreadsheet development four levels of measurement parametric statistics binomial probability chi-square contingency table Mann-Whitney U Test Kruskall-Wallis Test Spearman's Rank Correlation Excel statistics

Authors and affiliations

  • Warren Beatty
    • 1
  1. 1.University of South AlabamaMobileUSA

Bibliographic information