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Business Statistics for Competitive Advantage with Excel and JMP Basics, Model Building, Simulation, and Cases
Author
Title
Business Statistics for Competitive Advantage with Excel and JMP [electronic resource] : Basics, Model Building, Simulation, and Cases / by Cynthia Fraser.
ISBN
9783031425554
Edition
1st ed. 2024.
Publication
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Physical Description
1 online resource (XI, 285 p.) 375 illus., 69 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book is the latest title of the popular Excel textbook; redesigned, while including interactive, user-friendly JMP to encourage business students to develop competitive advantages for use in their future careers. How can performance outcome drivers be identified? How can performance outcomes be forecast? Use of regression, conjoint analysis, Monte Carlo simulation provide answers and solutions for specific scenarios. 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.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
April 10, 2024
Contents
Chapter 1. Statistics for Decision Making and Competitive Advantage
Chapter 2. Describing Your Data
Chapter 3, Hypothesis Tests and Confidence Intervals to Infer Population Characteristics and Differences
Chapter 4. Simulation to Infer Future Performance Levels Given Assumptions
Chapter 5. Simple Regression
Chapter 6. Finance Application: Portfolio Analysis with a Market Index as a Leading Indicator in Simple Linear Regression
Chapter 7. Indicator Variables
Chapter 8. Presenting Statistical Analysis Results to Management
Chapter 9. Nonlinear Regression Models
Chapter 10. Logit Regression for Bounded Dependent Variables
Chapter 11. Building Multiple Regression Models
Chapter 12. Model Building and Forecasting with Multicollinear Time Series
Chapter 13. Association Between Two Categorical Variables: Contingency Analysis with Chi Square
Chapter 14. Conjoint Analysis and Experimental Data.
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