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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.
Sommario
Chapter 1: An Introduction to Business StatisticsChapter 2: Descriptive StatisticsChapter 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 p
Info autore
Bruce L. Bowerman is professor of decision sciences at Miami University in Oxford, Ohio. He received his Ph.D. degree in statistics from Iowa State University in 1974, and he has over 40 years of experience teaching basic statistics, regression analysis, time series forecasting, survey sampling, and design of experiments to both undergraduate and graduate students. In 1987, Professor Bowerman received an Outstanding Teaching award from the Miami University senior class, and in 1992 he received an Effective Educator award from the Richard T. Farmer School of Business Administration. Together with Richard T. OConnell, Professor Bowerman has written 16 textbooks. These include Forecasting and Time Series: An Applied Approach; Forecasting, Time Series, and Regression: An Applied Approach (also coauthored with Anne B. Koehler); and Linear Statistical Models: An Applied Approach. The fi rst edition of Forecasting and Time Series earned an Outstanding Academic Book award from Choice magazine. Professor Bowerman has also published a number of articles in applied stochastic processes, time series forecasting, and statistical education. In his spare time, Professor Bowerman enjoys watching movies and sports, playing tennis, and designing houses.
