About This Chapter
Simulation in Quantitative Analysis - Chapter Summary and Learning Objectives
There is a certain amount of risk involved whenever you make a choice, and the field of quantitative analysis allows you to create simulations that give you the ability to predict which choices are riskier than others. In this chapter, our instructors give you the insider information about using quantitative analysis to further develop your decision-making skills. View the informative video lessons to discover the details concerning these key topics:
- Building simulations to solve problems
- The uses of computers during quantitative analysis
- Random numbers
- Probability distributions
- Running both static and dynamic simulations
- Applying the Monte Carlo simulation
|Using Simulation to Analyze and Solve Business Problems||Elaborate on how problems can be analyzed through the use of simulations.|
|The Role of Probability Distributions, Random Numbers & the Computer in Simulations||Discuss how computers, probability distributions, and random numbers have an intricate role in the model simulation process.|
|Static vs. Dynamic Simulation in Quantitative Analysis||List the differences between static and dynamic simulation.|
|The Monte Carlo Simulation: Scope & Common Applications||Analyze the Monte Carlo method, show how the method is impacted by randomness, and explain the uses for simulations using the Monte Carlo method.|
1. Using Simulation to Analyze and Solve Business Problems
This lesson covers using simulation to analyze and solve business problems. We'll learn about how simulation tools can help you to understand how a decision today can impact your company's success tomorrow.
2. The Role of Probability Distributions, Random Numbers & the Computer in Simulations
Computer simulations are valuable tools used to model complex systems. In this lesson we discuss random numbers and probability distributions in relation to their role in computer simulations.
3. Static Vs Dynamic Simulation in Quantitative Analysis
Quantitative Analysis uses models to present a projection of a situation if a certain decision is to be taken. A model is a representation of a real system used to test different entities of the system. In this lesson, you will learn about the two methods of quantitative analysis using models; static and dynamic simulation.
4. The Monte Carlo Simulation: Scope & Common Applications
This lesson will define Monte Carlo Simulations and briefly discuss their history and advantages, as well as how they're used to reduce the risk involved with complex decisions where outcomes are uncertain.
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