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1. |
Record Nr. |
UNINA9910300119503321 |
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Autore |
Beatty Warren |
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Titolo |
Decision Support Using Nonparametric Statistics / / by Warren Beatty |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
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ISBN |
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Edizione |
[1st ed. 2018.] |
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Descrizione fisica |
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1 online resource (XXII, 115 p. 60 illus.) |
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Collana |
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SpringerBriefs in Statistics, , 2191-544X |
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Disciplina |
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Soggetti |
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Statistics |
Operations research |
Decision making |
Business mathematics |
Big data |
Statistics for Business, Management, Economics, Finance, Insurance |
Statistical Theory and Methods |
Operations Research/Decision Theory |
Business Mathematics |
Big Data/Analytics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Preface -- Introduction to Decision-Making -- 1. Introduction to Variables and Sampling, Sampling Error, and Margin of Error -- 2. Introduction to Probability, the Foundation of Statistics, and Binomial Probability -- 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 -- Appendix of Tables Used -- References for Chapters 3-6 -- OpenOffice Help -- Spreadsheet Tutorial. . |
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Sommario/riassunto |
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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. 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. |
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