The dataset selected for this analysis is the 2015 College Football Statistics.
Domain Specific:
The rushing statistics of various players are provided. A rank is given to each player based on
Rushing Yards / Rushing Attempts. Other domain specifics characteristics are provided such as
player name, school, conference, rushing touchdowns, touchdowns from scrimmage, etc.
Data Abstraction:
This dataset can be abstracted as a flat table of items with a single key that maps to a number of
attributes. At any given point any of the single attributes or comparison between several attributes
migth be of interest, so there might be a need to filter, sort, or aggregate attributes for comparisons.
Domain Specific:
I wan't to be able to answer questions like the ones listed below.
Who has the most rushing attempts of all the listed players? Who has the most rushing yards of all the listed players? Who has the least plays from scrimmage? Are rushing attempts an indicator of player performance? Do more rushing attempts generally affect the number of yards gained by a single player in a rushing play?
Abstract:
As a user, I want to be able to discover distinct targets including individual values and extremes.
As a user, at any given point in time I want to be able to discover correlations between any two attributes.
-
Actions:
- Consume
- Discover
- Consume
-
Targets:
- One
- Individual Value
- Extremes
- Many
- Correlation
- Similarity
- Dependency
- One