Week |
Subject |
Related Preparation |
1) |
• Describe the course.
• Compare the difference between quantitative and qualitative analysis.
• Define the problem.
• Analyze how to develop a model.
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• Explain what quantitative analysis is.
• Explain what qualitative analysis is.
• Explain the quantitative analysis approach.
• List the three categories of business analytics.
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2) |
• Explain the advantages of mathematical modeling.
• Explain the mathematical models categorized by risk.
• Define the problem.
• Develop a model.
• Acquire input data.
• Develop a solution.
• Test the solution.
• Analyze the results.
• Identify the research problem.
• Analyze how to develop a quantitative analysis model.
• List the important issues in determining research question.
• List the possible problems in the quantitative analysis approach.
• Explain the quantitative analysis approach in the business life their relation to ethics.
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3) |
• Identify the decision theory.
• Identify the optimistic decision making under uncertainty.
• Identify the pessimistic decision making under uncertainty.
• Identify the criterion of realism (Hurwicz Criterion) decision making under uncertainty.
• Identify the equally likely (Laplace) decision making under uncertainty.
• Identify the minimax regret decision making under uncertainty.
• List the types of decision making under risk.
• List the six steps in decision making.
• Explain the types of decision making environments.
• Identify the decision making under uncertainty.
• List the types of decision making under uncertainty.
• Identify the decision making under risk.
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4) |
• Identify and explain the sensitivity analysis.
• Demonstrate how probability values are estimated by Bayesian analysis.
• Calculate the revised probabilities.
• Discuss the potential problems in using survey results.
• Illustrate how to measure utility and construct a utility curve.
• Identify the decision trees.
• Identify the utility theory.
• Explain the utility as a decision making criterion.
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5) |
• Illustrate how to use graphical representation of constraints.
• Analyze the isoprofit line solution method.
• Analyze the corner point solution method.
• Explain what slack and surplus is.
• Analyze linear programming models.
• List and explain the requirements of a linear programming.
• Formulate linear program problems.
• Illustrate how to use graphical solution to a linear program problem.
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6) |
• Analyze ‘no feasible solution’ case in linear program.
• Analyze ‘unboundedness’ case in linear program.
• Analyze ‘redundancy’ case in linear program.
• Analyze ‘alternate optimal solution’ case in linear program.
• Solve minimization problems.
• Analyze four special cases in linear program.
• Identify and explain the sensitivity analysis.
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7) |
• Identify and explain the marketing applications.
• Identify and explain the manufacturing applications.
• Identify and explain the employee scheduling applications.
• Identify and explain the financial applications.
• Identify and explain the ingredient blending applications.
• Identify and explain the transportation applications.
• Classify the linear programming applications.
• Formulate linear program problems.
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8) |
• Evaluate students via midterm exam
• Explain the advantages of mathematical modeling.
• Explain the mathematical models categorized by risk.
• Identify the criterion of realism (Hurwicz Criterion) decision making under uncertainty.
• Identify the equally likely (Laplace) decision making under uncertainty.
• Demonstrate how probability values are estimated by Bayesian analysis.
• Illustrate how to use graphical representation of constraints.
• Analyze the corner point solution method.
• Identify and explain the marketing applications.
• Midterm exam
• List the important issues in determining research question.
• List the possible problems in the quantitative analysis approach.
• List the types of decision making under uncertainty.
• Identify the decision trees.
• Formulate linear program problems.
• Illustrate how to use graphical solution to a linear program problem.
• Formulate linear program problems.
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9) |
• Analyze the transportation algorithm.
• Analyze the unbalanced transportation problems.
• Analyze the degeneracy in transportation problems.
• Analyze the more than one optimal solution.
• Analyze the maximization transportation problems.
• Analyze the unacceptable or prohibited routes.
• Analyze the unbalanced assignment problems.
• Analyze the maximization assignment problems.
• Analyze the transportation problem.
• Analyze the assignment problem.
• Analyze the transshipment problem.
• List and analyze the special situations with the transportation algorithm.
• Identify the facility location analysis.
• List and analyze the special situations with the assignment algorithm.
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10) |
• Identify and explain the maximal-flow technique.
• Identify and explain the shortest- route technique.
• Formulate and solve the linear program for maximal flow problem.
• Formulate and solve the linear program for shortest-route problem.
• Analyze network models.
• Analyze the maximal-flow problem.
• Analyze the shortest-route problem.
• Analyze the minimal-spanning tree problem.
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11) |
• Solve the model with binary variables.
• Identify and explain the nonlinear objective function and linear constraints.
• Identify and explain the nonlinear objective function and nonlinear constraints.
• Identify and explain the linear objective function with nonlinear contraints.
• Analyze integer programming.
• Analyze goal programming.
• Analyze nonlinear programming.
• Discuss the difference between goal programming and linear programming.
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12) |
• Explain what CPM is.
• Explain what PERT is.
• Illustrate how to draw the CPM/PERT network.
• Illustrate how to find the critical path.
• Calculate the probability of project completion.
• Identify and explain project management
• Identify and explain the sensitivity analysis.
• Compare the difference between CPM and PERT.
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13) |
• Analyze the planning and scheduling project costs.
• Identify and explain the monitoring and controlling project costs.
• List and explain the four steps of project crashing.
• Explain what subprojects is.
• Explain what milestones is.
• Analyze the PERT/Cost.
• Analyze the project crashing.
• Analyze the project crashing with linear programming
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14) |
• Identify and explain language of games.
• Identify and explain the minimax criterion.
• Identify and explain pure strategy games.
• Identify and explain mixed strategy games.
• Identify and explain dominance strategy games.
• Analyze game theory.
• List five types of games in game theory.
• Solve game theory problems with linear programming.
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15) |
• Evaluate students via final exam
• Analyze the transportation algorithm.
• Identify and explain the shortest- route technique.
• Solve the model with binary variables.
• Illustrate how to draw the CPM/PERT network.
• Illustrate how to find the critical path.
• Identify and explain dominance strategy games.
• Final Exam
• Analyze the transportation problem.
• Analyze the shortest-route problem.
• Analyze integer programming.
• Identify and explain project management
• Analyze game theory.•
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