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This concise volume covers nonparametric statistics topics that most are most likely to be seen and used from a practical decision support perspective.
The Decision Making Process: A brief look at decision-making itself
Section 1: Concepts Common to ALL Statistics
1) Introduction to Variables; and an Introduction to Sampling, Sampling Error, and Margin of Error
2) Introduction to Probability, the Foundation of Statistics, and to Binomial Probability
Section 2: The NonParametric Statistics Tools
3) One Population Hypothesis Testing: Nominal - Runs Test, Sign Test; Ordinal, Interval - Wilcoxon Signed Rank Test
4) Two Population Hypothesis Testing: Nominal - Sign Test, Chi-Square Contingency Table; Ordinal, Interval - Wilcoxon Signed Rank Test, Mann-Whitney U Test
5) Three or More Population Hypothesis Testing: Nominal - Chi Square Contingency Table; Ordinal, Interval - Kruskall-Wallis Test
6) Association: Nominal - Chi-Square Test of Association; Ordinal, Interval - Spearman's Rank Correlation
Section 3: Appendices and Miscellaneous
Appendix of Tables Used
References for Chapters 3-6
OpenOffice Help: OpenOffice Help and Compatibility with Excel Statistics Functions
Spreadsheet Tutorial: A Quick & Dirty Spreadsheet Tutorial
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.