Due: Sunday 11/14

This should be a document 1-2 pages in length that includes the following parts:

1. What question(s) you plan to address
2. The data set you will use
3. A group plan

You will submit your proposal on Gradescope using the group submission feature, just like prior group submissions.

Part 1: Introduction and Research Questions

Your proposal should begin by introducing your topic in general and then defining one or more research questions. Research questions are the guiding questions you want to answer or problems you want to solve in your project. Your research question(s) should be (1) substantial, (2) feasible, and (3) relevant.

1. Substantial research questions require more than a surface-level analysis (more than just computing basic summary statistics on readily available datasets, for example).
2. Feasible research questions can actually be addressed by four or five team members over the course of approximately six weeks using data you can access.
3. Relevant research questions address a subject of importance and interest within the scientific community or broader society.

You should provide a brief justification of your research question(s) with respect to each of these three points.

Part 2: Data Sources

Your project should deal with real data. We provide pointers to some data sources in the Project Ideas section of the group formation post, but you are welcome and encouraged to look for your own data sources. After your introduction and research questions, your proposal should discuss the data you will use to answer your research questions. Be as specific as possible: name the datasets you will use and how you will access them or specify where you will look for the relevant datasets and why you expect to be successful in finding them. You should also briefly justify why the data you plan to obtain will be relevant and appropriate for addressing your research questions. Searching for data sources as you refine your research questions is likely to be the most time-consuming part of preparing your proposal and is crucial for a good start on your project, so do not put it off.

Part 3: Group Plan

This should be similar to group 2’s plan and answers items 3 through 7. You of course can also have a team name (item 2).

Feedback and Grading Rubric

Proposals will be evaluated on the following criterion-based rubric. Proposals satisfying all criteria will receive full credit. Formative feedback (comments and suggestions) will also be provided for each proposal.

1. Satisfies general directions (length, on-time pdf submission, group submission, etc.)
2. Includes a brief introduction to the topic of interest
3. Poses one or more concrete research questions
4. Provides a reasonable justification that research questions are substantial
5. Provides a reasonable justification that research questions are feasible
6. Provides a reasonable justification that research questions are relevant
7. Includes one or more specific datasets or reasonable discussion of how to locate data
8. Provides reasonable justification that data sources are appropriate for research questions
9. Has a group plan that addresses (1) how you will communicate, (2) when, (3) where, and (4) how you will work together, and (5) a proposal of what happens if a team member cannot finish their planned work.

Due: Tuesday 11/9

For the final project, you will get to choose your own group of 3-4 people. You do not need to find a group if you do not know who you want to work with or you do not yet have enough members in your group. We will assign or form groups if needed. The form asks for project interest and we will match you to a group that aligns as close to your interests as possible.

When you are ready, you will need everyone’s names and netids. Fill out the group formation form. You may fill out this form with fewer people, which we will take as an indication of you want to be together and we will add more members to your group. If you have 3 people in your group, we may add a 4th to ensure everyone is in a group by the end of the group formation period.

Only fill this form out once per group. If your group fills this out more than once, we will take the last entry. Make sure to confirm with your group who is responsible for filling out the form.

This form collects the person filling it out already, so the questions are only for the other members of the group.

Project Ideas

It may help to start looking for project ideas and data sources as you form your groups.

Example Ideas

Not sure how to get started? Looking for examples of what a data science project might look like? Here are some of the topics that students studied in CS216 Spring 2020:

• Comparing Stock Market Losses between SARS and SARS-CoV-2
• Recessions, Depressions, and Depression: Mental Health in Relation to Economic Factors
• Predicting North Carolina Election Outcomes
• Relating Text Analysis of Corporate Reports and Stock Performance
• Modeling Consumer Flight Behavior Based on Economic Indicators
• Predicting COVID-19 Death Tolls from Google Search Trends
• Sentiment Analysis of COVID-19 Tweets
• Economic Status and Drug Overdose in North Carolina
• Analyzing Gender and Tech Careers
• Political Landscape According to Social Media
• Forecasting Market Shocks and Performance using Article Headlines
• Tracking Recidivism in US Prisons
• Understanding AirBnBs impact on Evictions
• Understanding Musical Tastes (Music Recommender System)
• Human Impact on Climate since the Industrial Revolution
• The Troll Toll: An Investigation into Troll Tweets

And here is an archive of summer Data+ projects from the last several years. In Data+, teams of about 4 undergraduate students collaborate over the summer on a data science project. You should be able to see final presentations and/or executive summary slides for most projects; feel free to browse for inspiration.

Example Data Sources

Below, we have some examples of datasets or where you might find data. You should work with data that is interesting to you and should feel free (strongly encouraged even) to look for sources yourself. These are listed just as possibilities and starting places.

• Kaggle maintains several thousand public datasets of interest in a variety of topics. Kaggle also hosts several prediction challenges; one idea for a machine learning project is to enter one of these competitions as a team.
• The Yelp Dataset is provided by Yelp as a research challenge with lots and lots of data about reviews, businesses, images, and cities – text data, rich json data, etc.
• The University of California Irvine maintains a large UCI ML repository of publicly contributed datasets aimed toward machine learning tasks of all types. They range from small simple example datasets to large and complicated datasets from specific scientific domains.
• Data.gov has a huge compilation of data sets produced by the US government. The US Census Bureau also publishes datasets from all of its survey work. Similarly, The Supreme Court Database tracks all cases decided by the US Supreme Court, and GovTrack.us provides links to all kinds of information about the US Congress and all votes casted by its members.

The zip file will be in the class Box folder in the Project folder. You will submit this as a group on Gradescope. This covers up to module 6. It is due Friday 10/29, late to Sunday 10/31.

To work collaboratively, you can choose to use Google Colab. Put the file in your Google Drive and share it with your group. When you open the file, it will open in Google Colab. You all should be able to work on the notebook at the same time. However, working within the same cell may not work. You may notice that the file locations for the data are over the internet, rather than local. This change is to make working with Colab easier, which does not hold onto the data files between uses.