Business Statistics for Competitive Advantage with Excel 2019 and JMP Basics, Model Building, Simulation and Cases /

• Κύριος συγγραφέας: Fraser, Cynthia (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Statistics .; Management.; Market research.; Statistics for Business, Management, Economics, Finance, Insurance.; Market Research/Competitive Intelligence.

 The revised Fifth Edition of this popular textbook is redesigned with Excel 2019 and the new inclusion of interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. Students learn to build models, produce statistics, and translate results into implications for decision makers. The text features new and updated examples and assignments, and each chapter discusses a focal case from the business world which can be analyzed using the statistical strategies and software provided in the text. Paralleling recent interest in climate change and sustainability, new case studies concentrate on issues such as the impact of drought on business, automobile emissions, and sustainable package goods. The book continues its coverage of inference, Monte Carlo simulation, contingency analysis, and linear and nonlinear regression. A new chapter is dedicated to conjoint analysis design and analysis, including complementary use of regression and JMP. 

 1. Statistics for Decision Making and Competitive Advantage -- 2. Describing your Data -- 3 Hypothesis Tests and Confidence Intervals to Infer Population Characteristics and Differences -- 4. Simulation to Infer Future Performance Levels Given Assumptions -- 5. Simple Regression for Long Range Forecasts -- 6. Finance Application: Portfolio Analysis with a Market Index as a Leading Indicator in Simple Linear Regression -- 7. Indicator Variables -- 8. Presenting Statistical analysis Results to Management -- 9. Nonlinear Regression Models -- 10. Logit Regression for Bounded Dependent Variables -- 11. Building Multiple Regression Models -- 12. Model Building and Forecasting with Multicollinear Time Series.-13. Association between Two Categorical Varaibles: Contingency Analysis with Chi Square -- 14. Conjoint Analysis and Experimental Data.