Week 7: Final Team Project

In Week 7, we will have our exam.

Exam

DA Exam Review (Optional)

In Week 8 we will have our final team project presentations (schedule).

Team Project
Each team will also give a 10-min final project presentation (instructions available here). Please confirm your presentation schedule with the instructor. You will also complete the final team project report - Get instructions here.

Click here for a sample report of descriptive analytics

Click here for a sample research study on prescriptive analytics

Click here for a sample student paper on predictive analytics

Click here for a sample student paper (it's a research paper)

This is a former student's research paper so you can see what a proper APA style paper looks like. His hypothesis statements follow the format that I expect from you. You should also see how he constructed his literature review, presented analysis results, drew conclusions, discussed limitations, etc. 

None of these papers are exactly what you should do for the Team Project, but they represent good models for parts of your project. We won't necessarily use the exact analyses presented in some of the papers (E.g., we won't be running advanced machine learning models as presented in the sample prescriptive analytics paper by two Stanford students.) Nevertheless, these papers give you a more concrete idea of what a good analytics report should look like and what you are expected to produce.

Below is a sample list of potential data sources for your team project organized by 14 industry sectors. Note that you should use the train (not test) dataset, if you're getting data from Kaggle. You should also feel free to search for datasets using Google's dataset search engine. 

Mason School's business library offers a number of databases that contain datasets:
  • Compustat | Execucomp (WRDS)
  • CRSP (WRDS)
  • Fitch Connect
  • Gallop Analytics
  • Global Data Explorer
  • Policy Commons
  • Sage Data
  • SEC Analytics (WRDS)
  • Refinitiv Eikon

All of these (and more) can be found on the W&M Libraries databases page at https://libraries.wm.edu/databases/by-type/1787. Feel free to contact the library for support.

You can even use datasets you have collected on your own, or from your prior/current workplace(s) (with permission.) 

In Week 2, Your team will submit TP01, which includes Introduction (i.e., team project topic), and a dataset for instructor approval. Your final dataset should consist of at least 200 cases, 3 numeric variables and 3 categorical variables from the last 10 years. See team project instructions here.

Food & Drinks
Active Duty Military (Data USA)

Automobile
Automobile prices
FRED Producer Price Index by Commodity: Real Estate Services (Partial): Office Buildings, Gross Rents

Government/Economics
All data related to Economic activity and social change in the UK, real-time indicators: 2 November 2023
Household Debt & Credit by Federal Reserve Bank of New York (Python tutorial by Bamboo Weekly)

Energy

Technology
Corporate Credit Rating with Financial Ratios (Kaggle)
Bitcoin Transactions (Kaggle)
Subscribe to: Posts (Atom)