This dataset is based on the Fuel economy data from 1999 to 2008 from `ggplot2`, but every value is represented by a distribution. Every variable in the data set is represetned by a categorical, discrete, or continuous random variable. The original MPG dataset in ggplot is a real a subset of the fuel economy data from the EPA, but the uncertainty is hypothetical uncertainty for each data type, added by us for illustrative purposes.
Format
A data frame with 234 rows and 11 variables:
- manufacturer
manufacturer, as a categorical random variable
- model
model name as a categorical random variable
- displ
engine displacement, as a uniform random variable to represent bounded data
- year
year of manufacture, as a sample of possible years
- cyl
number of cylinders, as a categorical random variable
- trans
type of transmission, as a categorical random variable
- drv
the type of drive train, as a categorical random variable
- cty
city miles per gallon, as a discrete random variable
- hwy
highway miles per gallon, as a discrete random variable
- fl
fuel type, as a categorical random variable
- class
"type" of car, as a categorical random variable