Group project for TSCI5230

Good news: You have been invited to be part of Prof. Elemental's grant-writing team. He sent each of you a COP comitting to 75% coverage of your salary, which will impress the promotion & tenure committee and make your department chair very happy with you. If this grant gets funded, of course.

Bad news: The grant is due December 15th.

Good news: You're only responsible for the preliminary data section.

Bad news: The previous data science team was suddenly hired away by Epoch Corporation, signing some kind of nasty non-compete agreement which prevents them from talking to Professor Elemental or any of his collaborators (i.e. you). All they left behind was this repo on GitHub that Professor Elemental managed to fork before they deleted it: https://github.com/bokov/FA21TSCI5230_project

Good news: This is the day for which the Translational Science & Clinical Investigation Program has been preparing you! You got this. Maybe you don't remember every single bit of information from your classes, but you are not alone-- you're working with three other excellent investigators-- they might remember the parts you forgot and vice versa. Furthermore, you can use Google, various R and Python help files, and any other source of information you can find.

Instructions:

• The file Grand_Draft.docx needs to be completed with the highlighted information. Instead of manually editing this file, you should generate a dynamic version of it using RStudio or some other means, as long as the original text is preserved, the format is reasonably similar, and of course you fill in the requested information.
• Submit your changes as pull requests to the bokov/FA21TSCI5230_project repository on GitHub. The course director will play the role of Professor Elemental and accept your pull requests (or in some cases request changes before accepting).
• When the project is complete, this repository should contain everything needed to verify your results by running your scripts as-is. It should also be possible to run your scripts on different input data (in the same format) without having to edit any files in this repository.
• Though FA21_TSCI5230_project.py contains useful information, you don't have to do the whole project in Python. You could pull the data into R and do some or all of the analysis there. You could even replace the Python script with equivalent R commands and not use Python at all.
• As a team, make a list of tasks that need to be done to complete the preliminary data section for this grant. Make note of which tasks depend on which other tasks. You could use GitHub issues to manage these tasks.
• If you are not working on a task, pick one from the list and check it off when you are done. Then choose another task. You can also add tasks to the list as you realize they are needed.
• We've been light on homework this semester, but for this final project you are expected to put in some work between classes and communicate with each other in order to avoid duplicating effort and to help classmates out when they get stuck.