Exam 1: Introduction to Modeling and Decision Analysis
Exam 1: Introduction to Modeling and Decision Analysis78 Questions
Exam 2: Introduction to Optimization and Linear Programming76 Questions
Exam 3: Modeling and Solving Lp Problems in a Spreadsheet93 Questions
Exam 4: Sensitivity Analysis and the Simplex Method76 Questions
Exam 5: Network Modeling92 Questions
Exam 6: Integer Linear Programming102 Questions
Exam 7: Goal Programming and Multiple Objective Optimization81 Questions
Exam 8: Nonlinear Programming Evolutionary Optimization87 Questions
Exam 9: Regression Analysis93 Questions
Exam 10: Data Mining125 Questions
Exam 11: Time Series Forecasting125 Questions
Exam 12: Introduction to Simulation Using Analytic Solver Platform85 Questions
Exam 13: Queuing Theory97 Questions
Exam 14: Decision Analysis125 Questions
Exam 15: Project Management Online82 Questions
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Which of the following categories of modeling techniques involves determining the value of a dependent variable based on specific values of independent variables?
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In which step of the problem-solving process is the main focus to generate and evaluate alternatives?
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The notion that every problem is also an opportunity is reflected in the term
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Humans usually do not make errors in estimation due to anchoring and framing effects.
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A factor that plays a role in determining whether a good or bad outcome occurs is called
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Virtually everyone who uses a spreadsheet today for model building and decision making
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In a decision-making framework presented in Chapter One, the term "dumb luck" refers to a situation when the following occur:
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A situation when decision quality is good and the resulting outcome quality is bad is referred to as
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Which of the following categories of modeling techniques addresses uncertainty in the values of the independent variables?
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Which of the following fields of study is defined in Chapter One as the one that "uses computers, statistics, and mathematics to solve business problems"?
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