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.
For access to accompanying data sets, please email author Cynthia Fraser at cfg8q@virginia.edu.
Edition
Language
Place of publication
Publishing group
Springer International Publishing
Illustrations
4 s/w Abbildungen, 341 farbige Abbildungen
XII, 417 p. 345 illus., 341 illus. in color.
Dimensions
Height: 279 mm
Width: 210 mm
Thickness: 24 mm
Weight
ISBN-13
978-3-030-20373-3 (9783030203733)
DOI
10.1007/978-3-030-20374-0
Schweitzer Classification
Cynthia Fraser
received her Ph.D. in marketing and econometrics from The Wharton School, University of Pennsylvania, and is a member of the Marketing faculty at The McIntire School of Commerce, University of Virginia, where she teaches business statistics. Her research has appeared in a number of journals, including
Decision Science, Management Science, Journal of Marketing, Journal of Consumer Research, Psychology and Marketing, Journal of International Business Studies,
and
Journal of Applied Social Psychology.
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.
