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Full Description
Bowerman and O'Connell's, "Essentials of Business Statistics" (EBS) delivers clear and understandable explanations of business statistics concepts through the use of case studies and examples. The non-calculus-based approach thoroughly covers descriptive and inferential statistics with an emphasis on business applications. Both procedural and conceptual aspects of the subject are covered, analysis and interpretation are emphasized, and shows students how to select the appropriate statistical tool for use in a particular business application. The abundant examples reflect real applications of statistics relevant to business students. A key distinction of EBS is the rich and realistic continuing case study examples that provide the architecture of the text.Unlike virtually all other texts, which use discreet examples for each individual subject area, EBS relies on these continuing examples to 'frame' the study of statistics and place it squarely into the realm of real business problems and scenarios. Part and parcel with this approach are the rich and relevant data sets used to demonstrate statistical concepts.Finally, Bowerman and O'Connell also provide a fresh technology perspective. Excel and Minitab output is included in the text to help students visualize concepts, and a robust Excel add-in package, Megastat is both available on the accompanying CD ROM and has been thoroughly integrated into the text. The coverage of the Internet included in the book is second to none.
Contents
Chapter 1StatisticsChapter 3: ProbabilityChapter 4: Discrete Random VariablesChapter 5: Continuous Random VariablesChapter 6: Sampling DistributionsChapter 7: Confidence IntervalsChapter 8: Hypothesis TestingChapter 9: Comparing Population MeansChapter 10: Comparing Proportions and Chi-Square TestsChapter 11: Simple Linear Regression AnalysisChapter 12: Multiple Regression And Model BuildingAppendix A: Statistical TablesAppendix B: Counting RulesAppendix C: The Hypergeometric DistributionAppendix D: Properties of the Mean and the Variance of a Random Variable, and the CovarianceAppendix E: Derivations of the Mean and Variance of x and pNER(01): WOW