關於本電子書
The term "decision analysis" (DA) refers to the academic field that encompasses the theory, technique, and professional practice that are required to tackle significant decisions in an organized fashion. It is possible to prescribe a recommended course of action by applying the maximum expected-utility axiom to a well-formed representation of the decision. Additionally, decision analysis includes many procedures, methods, and tools for translating the formal representation of a decision and its corresponding recommendation into insight for the decision maker, as well as for other corporate and non-corporate stakeholders.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Decision Analysis
Chapter 2: Decision Theory
Chapter 3: Multiple-criteria Decision Analysis
Chapter 4: Expected Value of Sample Information
Chapter 5: Decision-making Software
Chapter 6: Robust Decision-making
Chapter 7: Expected Value of Including Uncertainty
Chapter 8: Decision Quality
Chapter 9: Value Tree Analysis
Chapter 10: Bayesian Inference in Marketing
(II) Answering the public top questions about decision analysis.
(III) Real world examples for the usage of decision analysis in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of decision analysis' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of decision analysis.
