FINAL PROJECT:Structures and Arguments > Analyzing UMD Faculty Salary Data

Beginning: Hook audience with short introduction (use problem statement) and let the data analysis do the rest of the work.

Middle: Various data wrangling and tidy data techniques. Will comment the portions of code that are not exactly obvious.

End: Save some of the more compelling graphics for the end and use with short conclusion.

LOGOS: Data on UMD faculty salaries from past 5 years.
PATHOS: Will feature some professors who have thoughts on faculty salaries in order to add to motivation of this data analysis.

ETHOS: Credibility of myself and group members (have studied CMSC320 all semester), my data science professor (J.P. Dickerson), and other featured professors (Mb Shea).

STRUCTURE: I will use two features of Jupyter iPython notebooks: 1) Code cells and 2) Markdown cells.

GOAL: To demonstrate the power of data science protocols given a dataset.
December 4, 2017 | Unregistered CommenterAC
A, I will need to be careful as a featured professor BUT I can direct you how to share that information with a group of PTK professors who need clear information on salary comparisons.

Will part of your project be the generation of visuals that SHOW what the data SAYS?

Can you easily print from Jupyter iPython notebooks?

Mb
December 5, 2017 | Registered CommenterMarybeth Shea