Название: Business Statistics for Competitive Advantage with Excel 2019 and JMP: Basics, Model Building, Simulation and Cases
Автор: Cynthia Fraser
Издательство: Springer
Год: 2019
Страниц: 419
Язык: английский
Формат: pdf (true)
Размер: 52.1 MB

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.

Statistics and their potential to alter decisions and improve performance are important to you. With more and better information from statistical analysis, you will be equipped to make superior decisions and outperform the competition. You will find that the competitive advantages from statistical competence are powerful and yours.

This text features widely available Excel software, including many commonly used shortcuts. Excel is powerful and user friendly. For cases in which Excel does not offer the desired analyses, JMP is featured to supplement. Appendices with screenshots follow each chapter to make software interactions simple. Recreate the chapter examples by following the steps in the Excel sections. This will give you confidence using the software. Then forge ahead and generalize your analyses by working through end of chapter assignments. The more often you use the statistical tools and software, the easier analysis becomes.

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.​