The goal for the final project is for you to utilize the tools, techniques, and ideas from the class to make some type of quantitative decision. The following instructions must be followed in order to receive full credit towards your final project.
There are two deliverables that need to be submitted with your project:
An excel sheet that includes your data and decision making model
A word document that explains your data, how you collected it, and how your decision model works.
The following are the requirements for each of the deliverables:
Excel Sheet with Decision Making Model Requirements
Your decision making model must make some type of quantitative decision.
We have mostly discussed business/start-up types of decisions, however, you are free to choose any type of quantitative decision.
Your decision making model must be using a data set that includes at least 50 observations for four different variables.
You may use other variables that have less observations in addition to the four required above.
You may use multiple sources for your data for the four required or any optional additional variables.
**TIP** Think back to the multiple ways we talked about collecting data. Primary data collection is an option, but you can also use secondary data that is publicly available.
**ANOTHER TIP** Remember that sometimes you can model a variable even if you do not have data on it if you have summary statistics along the lines of averages, SD, assumptions about distributions, etc...
Your decision making model must be informed by at least two of the following analytical techniques we have used in class:
Distribution Analysis (Histograms, Skewness, and Kurtosis)
Your decision making model must utilize Monte Carlo analysis.
**TIP** The analytical techniques should help your form some of the assumptions of the Monte Carlo along with how the metrics/variables interact with each other in the Monte Carlo itself.
Word Document Requirements
A introductory section that describes the exact quantitative decision you would like to be able to make with your model.
A section that explains the exact variables you collected data on and how you collected that data (including the sources).
A section that explains what variables/metrics that you are including in your decision making model.
A section that describes the steps you went through to put together your decision making model. This should include:
How you arrived at all of the assumptions behind your model.
**TIP** This is probably where you would use your analytical techniques to inform your assumptions.
How the model actually works in terms of running the Monte Carlo.
**TIP** This is probably where you would use your analytical techniques to inform how your variables/metrics interact.
What the different findings and outcomes of the model are.
How the findings/outcomes of the model help in making the decision you set out to make.