Submission rules

• One student cannot submit multiple projects
• The length of a project can be at most 5 pages
• There can be at most 5 authors of the project (the student who submits the project, plus at most 4 coauthors)
• Each project must be sponsored by a faculty member, who will attest that the student(s) did complete the project themselves and were undergraduates when they did the work
• Each faculty member can sponsor at most 5 projects for the competition. If more than 5 projects are submitted for a faculty member, then they will be asked to choose their top 5 projects for judging

Judging rules

• Judges must be university faculty, graduate students, or industry professionals
• Each judge can score at most 6 projects
• Every project must be scored by at least 5 judges
• Each project is scored on the following criteria. Each criterion is worth 10 points:
  • Introduction: how well the students introduce and motivate the problem
  • Methods: are the chosen statistical methods sufficient and appropriate to address the research question?
  • Interpretation: do the students use and interpret their statistical results correctly?
  • Discussion: do the students discuss their results and conclusions in the context of the research problem?
  • Discretionary: each judge can award additional discretionary points for projects they believe are particularly worthy of praise
• Judges scores will be combined to determine 1st place, 2nd place, and 3rd place winners of the competition. It will be up to you to decide how to appropriately combine these scores

Provided data

In the GitHub repository, you are provided with 5 CSV files:

• faculty_info.csv: the name and email address of the faculty members sponsoring the student projects in this competition
• judge_info.csv: the name, judge ID, and role (faculty, graduate student, etc.) of everyone who volunteered to judge this competition
• judge_scores.csv: scores from the judges on their assigned projects.
  • Note: part of your task will involve you assigning judges to projects. You will almost certainly make different assignments than what I did here. That is ok! You will just use the judge_scores.csv file to find the winners
• student_submissions.csv: information about the different student submissions to the competition
• verification_responses.csv: information provided by faculty sponsors when asked to verify their students’ submissions

Part 1: Send verification emails

The email addresses included in the faculty_info.csv file really work (they all go to me). Your first task is to email each faculty member with information about the project(s) submitted by their students; each sponsor is asked to (1) verify their students’ work, and tell us if any projects should be disqualified, and (2) choose their top 5 projects, if they have more than 5 projects submitted to the competition.

Here is an example of what the email should look like:

Requirements:

• The student information for each faculty sponsor must be included as a table in the email, as shown in the example
• The emails must be generated and sent automatically, using R. You are not allowed to write the emails all separately by hand. Rather, you must write a script that fills in the email template with the information for each faculty member (their name, the number of projects submitted, and a table of the student information), then sends the emails
  • I would recommended looking at the mailmerge and gmailr packages for this step
• The emails must be sent to the faculty email addressed in the faculty_info file. If correctly sent to these email addresses, they will be forwarded to my inbox, so I will be able to check. Make sure to sign your names!

Part 2: Assign judges

Now that you have received submission verification from the faculty members, it is time to assign judges to the projects. Your task in this part is to produce a table, which you will write to a CSV file called judging_assignments.csv.

Requirements:

• Judging assignments should obey the judging and competition rules described above
• You may not waste judges’ time: do not send them inadmissible projects, and do not assign too many projects to any judge
• Your judging_assignments.csv file should contain one row for each judge assigned to the projects, with the following columns:
  • judge_name: the name of the judge
  • judge_id: the judge’s ID number, corresponding to the judge_id column in the judge_info.csv file
  • A column for each project the judge is assigned, containing the project ID number. Reading across the row for each judge will tell me which projects were assigned to that judge

Part 3: Winning projects

Now that we have the judging scores, we can go ahead and identify the winners! Using the scores, your task is to create a table containing the 1st, 2nd, and 3rd place winner information. Your table should have three rows (one for each winner), and the following columns:

• Award: whether the project won 1st, 2nd, or 3rd place
• ID: the ID of the project
• Student: the full name of the student who submitted the project
• Coauthors: the names of any co-authors on the project
• Faculty: The full name of the faculty sponsor for the project
• School: the school which the students attend

You will save this information in a CSV file called winning_projects.csv.

Requirements:

• It is up to you to figure out how to combine judging scores to determine the winning projects. However, your choice must be statistically sound and defensible

Other requirements

Code:

• All code needed to reproduce the work must be included in the repository and pushed to GitHub. This includes the code for emailing the faculty sponsors, assigning judges, and determining winners.
• Any additional files you create, such as judging_assignments.csv and winning_projects.csv, must also be included in the GitHub repository
• You may not modify any of the original CSV files I provide
• Your code should be organized and commented. Consider dividing different tasks between different files. Consider using appropriate helper functions when needed.

Contributions and sources: Include a README.md in the repository which describes:

• The contributions for each group member
• Any outside resources used (provide citation for things like R package documentation, discussion forum posts that were helpful, etc.)
• Any use of generative AI. Your disclosure should state what program you used and how you used it, including links to the specific prompts you used, if possible. Properly citing the AI-generated content allows me to understand your process better and gives credit to the assistance received from these tools.