Fraser Business Statistics for Competitive Advantage with Excel 2007

Basics, Model Building and Cases
Erscheinungsjahr 2008
ISBN: 978-0-387-74403-2
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 410 Seiten, eBook

Exceptional managers know that they can create competitive advantages by basing decisions on performance response under alternative scenarios. To create these advantages, managers need to understand how to use statistics to provide information on performance response under alternative scenarios. Statistics are created to make better decisions. Statistics are essential and relevant. Statistics must be easily and quickly produced using widely available software, Excel. Then results must be translated into general business language and illustrated with compelling graphics to make them understandable and usable by decision makers. This book helps students master this process of using statistics to create competitive advantages as decision makers. Statistics are essential, relevant, easy to produce, easy to understand, valuable, and fun, when used to create competitive advantage. The Examples, Assignments, And Cases Used To Illustrate Statistics For Decision Making Come From Business Problems McIntire Corporate Sponsors and Partners, such as Rolls-Royce, Procter & Gamble, and Dell, and the industries that they do business in, provide many realistic examples. The book also features a number of examples of global business problems, including those from important emerging markets in China and India. It is exciting to see how statistics are used to improve decision making in real and important business decisions. This makes it easy to see how statistics can be used to create competitive advantages in similar applications in internships and careers. Learning Is Hands On With Excel and Shortcuts

Zielgruppe

Graduate

Autoren/Hrsg.

Fraser, Cynthia

Inhaltsverzeichnis

Statistics for Decision Making and Competitive Advantage.- Describing Your Data.- Hypothesis Tests, Confidence Intervals and Simulation to Infer Population Characteristics and Differences.- Quantifying the Influence of Performance Drivers and Forecasting: Regression.- Marketing Segmentation with Descriptive Statistics, Inference, Hypothesis Tests and Regression.- Finance Application: Portfolio Analysis with a Market Index as a Leading Indicator in Simple Linear Regression.- Association between Two Categorical Variables: Contingency Analysis with Chi Square.- Building Multiple Regression Models.- Model Building and Forecasting with Multicollinear Time Series.- Indicator Variables.- Nonlinear Multiple Regression Models.- Indicator Interactions for Structural Differences or Changes in Response.- Logit Regression for Bounded Responses.