
Business Analytics Principles, Concepts, and Applications with SAS
Description
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Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives.
They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making.
Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning.
Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself.
Business Analytics Principles, Concepts, and Applications with SAS will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.
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Persons
Dara G. Schniederjans is an assistant professor of Supply Chain Management at the University of Rhode Island, College of Business Administration. She has published articles in journals such as Decision Support Systems, Journal of the Operational Research Society, and Business Process Management Journal. She has also coauthored two text books and coedited a readings book. She has contributed chapters to readings utilizing quantitative and statistical methods. Dara has served as a guest coeditor for a special issue on Business Ethics in Social Sciences in the International Journal of Society Systems Science. She has also served as a website coordinator for Decisions Sciences Institute. She currently teaches courses in Supplier Relationship Management and Operations Management.
Christopher M. Starkey is an economics student at the University of Connecticut-Storrs. He has presented papers at the Academy of Management and Production and Operations Management Society meetings. He currently teaches courses in Principles of Microeconomics and has taught Principles of Macroeconomics. His current research interests include macroeconomic and monetary policy, as well as other decision-making methodologies.
Content
PART I: What Is Business Analytics? 1
Chapter 1: What Is Business Analytics? 3
PART II: Why Is Business Analytics Important? 15
Chapter 2: Why Is Business Analytics Important? 17
Chapter 3: What Resource Considerations Are Important to Support Business Analytics? 29
PART III: How Can Business Analytics Be Applied? 43
Chapter 4: How Do We Align Resources to Support Business Analytics within an Organization? 45
Chapter 5: What Is Descriptive Analytics? 63
Chapter 6: What Is Predictive Analytics? 95
Chapter 7: What Is Prescriptive Analytics? 117
Chapter 8: A Final Business Analytics Case Problem 137
PART IV: Appendixes 161
Appendix A: Statistical Tools 163
Appendix B: Linear Programming 195
Appendix C: Duality and Sensitivity Analysis in Linear Programming 229
Appendix D: Integer Programming 249
Appendix E: Forecasting 257
Appendix F: Simulation 281
Appendix G: Decision Theory 289
Index 321
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