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29 Assignment 5

* Due by December 1st at 4:30 p.m. *

The assignment is worth 10% of your final grade. Your assignment should be submitted through Moodle.

CONTENT

  • Dashboard [Team] – 10 points

This is a team assignment. Everyone is expected to contribute.

Be sure to keep meeting minutes that clearly describe each team member’s responsibilities. This includes outlining who has agreed to do what, and when everyone has agreed to share work so that it can be collated and prepared for final submission. As a team, you should also consider discussing and documenting the expectations you have of each other. These notes will help you should you have any issues arise throughout the semester. Submit your dashboard (team).

Create a dashboard in R Shiny (or Python) to share the results of your semester-long work. Your dashboard must contain the following elements:

  • [1%] A short description of the problem, including the questions that your dashboard will answer.
  • [1%] A short literature review that outlines the problem. The literature review should be accessible by non-academic community members, and properly cited.
  • [3%] An accessible description of the methods that are used. All methods must be mentioned. Two of the methods must be described in detail (with appropriate citations), including “demos” of how the methods work, and how the reader should interpret the findings.
  • [3%] Different visualizations of the data that help to answer each of your questions. There should be information provided with each visualization that interprets what the reader is viewing, as well as links to all data sources used. It should also describe any limitations. Note: If the data are dynamic (such as with ongoing COVID-19 cases and death counts), you should provide enough information to the reader so that they can easily interpret the findings as things change.

Finally, your dashboard must be

  • [2%] well organized, clear, concise, aesthetically interesting, and engaging. Grammar and spelling count.

A sample dashboard that I created during the early months of the COVID-19 pandemic can be found here.

License

Community Engaged Data Science Copyright © 2023 by Daniel Gillis. All Rights Reserved.