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Decision Support Using Nonparametric Statistics

  • Book
  • © 2018

Overview

Authors:
  1. Warren Beatty

    1. University of South Alabama, Mobile, USA

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  • Shows why analysis using nonparametric statistics is always valid and why using them will lead to better decision-making
  • Offers brief, practical, and to-the-point guidance on business data analysis and decision-making
  • Presents a brief introduction to Decision Making
  • Provides downloadable supplementary material: annotated spreadsheets, OpenOffice help, and exercise data and solutions

Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-xxii
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  2. The Decision Making Process

    • Warren Beatty
    Pages 1-2

  3. Four Facts About ALL Statistics

    • Warren Beatty
    Pages 3-3

  4. Introduction

    • Warren Beatty
    Pages 5-16

  5. Four Levels (Scales) of Data Measurement

    • Warren Beatty
    Pages 17-22

  6. Variables, Random Variables, and Variable Characteristics, Sampling

    • Warren Beatty
    Pages 23-28

  7. Probability and the Binomial Probability Distribution

    • Warren Beatty
    Pages 29-42

  8. One Population Hypothesis Testing

    • Warren Beatty
    Pages 43-54

  9. Two Populations

    • Warren Beatty
    Pages 55-78

  10. Three (or More) Populations

    • Warren Beatty
    Pages 79-85

  11. Association

    • Warren Beatty
    Pages 87-96

  12. Erratum to: Decision Support Using Nonparametric Statistics

    • Warren Beatty
    Pages E1-E1

  13. Back Matter

    Pages 97-115
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Keywords

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.

Authors and Affiliations

  • University of South Alabama, Mobile, USA

    Warren Beatty

About the author

Warren Beatty, PhD, was Professor of Management (retired) at the University of South Alabama College of Business, where he developed the Department of Management's curriculum on Business Decisions.  During his tenure there, Professor Beatty was central to the university's development and usage of the Statistical Package for the Social Sciences (SPSS) and of the Statistical Analysis System (SAS).  He received a B.S. in Statistics from Mississippi State University, an MBA from the University of South Alabama, and a Ph.D. in Quantitative Management and Decision Making (with a minor in Statistics) from Florida State University.  Professor Beatty has authored over forty refereed journal articles and was a consultant to many Gulf Coast businesses and governments for over thirty years in the areas of computer selection and implementation, statistics and its use in analysis and decision support, and the decision process itself. 




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