Statistics Project

 
 
Guidelines
A key learning objective of this course is for you to be able to apply what you learn to solve novel problems that you encounter in your professional setting. As such, the final exam for this course is an individual project that integrates and applies the techniques covered in the course in a unique problem.

• The project deadline is Friday, May 20, 2022.
• You will have 5 minutes to briefly present your project in class on Thursday, May 12^th.

 
TOPIC
Think about a domain you are very interested and/or experienced in and then think about aspects of it that are economic – issues of supply and demand, cost and profit, inventory management, appreciation/depreciation of value, entrepreneurial strategy, etc. What problems do you see in that domain that could benefit from an analytic model? Think outside the box and don’t hesitate to contact me if you need help or if you want feedback from me at any time.
Below is an outline of what material I expect to see in you final project report.
 
GENERAL LOGISTICS:
As a reminder, these are INDIVIDUAL projects, and I will be expecting a unique submission from each student.
Write your report in Word using double line spacing.

1. Save your data, model and analysis in an Excel file. Use label and sheet names to clearly organize your Excel file.
2. Paste any relevant table and chart in your report including labels and references in the text.
3. Use font Arial size 10 (or similar if not available in your system).
4. By midnight on the due date, upload your Word file and Excel data file in Sakai under Assignments. (10% of the points will be deducted for each day or fraction of day that work is submitted after the due date.)

 
 
You should plan to write a brief report (3-5 pages) that has the following sections:
Introduction – describe the problem you are trying to solve (e.g., What/when should I buy and sell shares in Stock X based on historical data? When should inventory be put on sale?), with some description of the topic domain (e.g., venture capitalism, clothing retail, restaurant management). Your problem should be rich enough to require a spreadsheet model and simulation or linear optimization.
Analytic Strategy – verbally describe your model/s of the problem, but also include an influence diagram and mathematical model, the assumptions your model/s make/s about the problem and the variables that are involved; also describe what data you will be using and how you will acquire it.
Findings and Implications – provide a visual model of the data and/or the model output/analytic results and a verbal explanation for what they mean to a decision maker faced with the problem you analyzed. If you had been hired by someone to consult on this problem, how you would advise them to act based on your findings.
References – provide verifiable citations for any published studies or documents that informed your project, as well as any external data set/s that you used to complete it.
 
 
Rubic: