The final project will give you the opportunity to test the knowledge of what you have learned throughout the course on a real dataset.

The project will involve outlining some main research question(s), carrying out some descriptive and inferential statistical analysis, regression modelling and a brief summary of your findings.

IMPORTANT: Any research question that you think is interesting and that can lead to a statistical analysis is fair.

You will have the choice of picking one of the following projects (Click in each link to know more details on the project):

SUBMISSION

The final project will be fetched, completed and submitted similarly to an assignment. In order to do this, and as a reminder, you will need to do the following steps:

  1. Log in on the server with your Andrew ID as the username, and the password that you guys chose the first day.
  2. Go to the assignments tab.
  3. Click on the “fetch” button.
  4. Now both projects have been downloaded. Click on the project that you picked and complete it.
  5. After its completion, go back to the Downloaded assignments and press “Submit”.

If you are unsure about how to perform these steps, I recommend visiting the menu materials in this webpage, where you’ll find a short video demonstration on how to fetch, download and submit assignments.

HONOR CODE

You may not discuss this project in any way with anyone besides the professor and TA. Failure to abide by this policy will result in a grade equal to 0.

You can still of course ask general coding questions either on Piazza, via email or during office hours. But please don’t post a large block of code and then ask “why doesn’t this work?”

TIPS

The project is an opportunity to apply what you guys have learned about descriptive and inferential statistics, regression modelling, and hypothesis testing.

The goal is NOT to do an exhaustive data analysis, that is do NOT try to calculate every statistic and procedure you have learned for every variable. Instead, try to show that you can efficiently use R to analyze data, and that you can interpret and present the results.

You might consider critiquing your own research, such as issues pertaining to the data and the appropriateness of the statistical analysis you used within the context of this project.