measurement_scale.RdThe 5 options for measurement scales which can be appended to the dataset.
A helper data object to be used with create_attribute.
measurement_scaleA named list, keys are named the same as values.
nominal: Used to define categorical scale attributes. Nominal is used when numbers have only been assigned to a variable for the purpose of categorizing the variable. An example of a nominal scale is assigning the number 1 for male and 2 for female.
ordinal: Used to define ordered scale attributes. Ordinal is used when the categories have a logical or ordered relationship to each other. These types of scale allow one to distinguish the order of values, but not the magnitude of the difference between values. An example of an ordinal scale is a categorical survey where you rank a variable 1=good, 2=fair, 3=poor.
interval: Used to define interval scale attributes. Intervals define data which consist of equidistant points on a scale. For example temperature data, mark grading, IQ scale, etc. Intervals can be negative while ratios cannot
ratio: Used to define ratio scale attributes. Ratios define data which consists not only of equidistant points but also has a meaningful zero point, which allows the ratio to have meaning. For example measurement heights, flow rates, weight, length, etc.
dateTime: Used to define date and time attributes. DateTime is used when the values fall on the Gregorian calendar system. DateTime values are special because they have properties of interval values (most of the time it is legitimate to treat them as interval values by converting them to a duration from a fixed point) but they sometimes only behave as ordinals (because the calendar is not predetermined, for some dateTime values one can only find out the order of the points and not the magnitude of the duration between those points). The most encompassing format is: YYYY-MM-DDThh:mm:ss.
measurement_scale$nominal #"nominal"
#> [1] "nominal"