Project

This course includes a project. This project should align with the course objectives. A well done project will demonstrate that the author has mastered the use of spreadsheets as outlined in these objectives.

There is considerable latitude in the project. A simple direction is to find a large dataset and perform a basic analysis using a spreadsheet. Other options are available and include implementing a simulation, or building a set of advanced tools in a spreadsheet. If you are considering a unique direction for your project please consult with the instructor.

A large dataset project should include a raw data set with

• At least 1,000 records (or rows)
• At least 10 useful fields (or columns)
  • 2-3 fields containing numeric data that is used in the analysis.
  • 2-3 fields containing text data that is used in the analysis.
  • At least one date/time field.

An ideal data set will

• Require a number of derived or computed fields.
• Be spread across several tables.

In general, I would much rather have you perform a partial analysis of a large dataset then a complete analysis of a trivial data set.

Components

1. Project proposal paper (15%) and presentation (5%) , due 2/20
2. Progress report (5%) and presentation (5%), due 3/26
3. Final report (20%) and presentation(10%), due 4/21.
4. Reproducible research document and workbook(s) (40%), due 4/21

Please note, submission instructions and rubrics will be provided before the projects are due.