Variable Statistical Types

A variable can have several statistical types:

Type	Description	Example
Continuous	Values are numerical, continuous, and sortable. They can be used to calculate measures; for example, mean or variance. During modeling, a continuous variable may be grouped into significant discrete bins.	The variable `<salary>` is both a numerical variable, and a continuous variable. It may, for example, take on the following values: `<$1,050>`, `<$1,700,>` or `<$1,750>`. The mean of these values may be calculated.
Ordinal	Values are discrete. They can be regrouped into categories and are sortable. Ordinal variables may be: Numerical: the values are numbers and they are ordered according to the natural number system (0, 1, 2, and so on). Textual: the values are character strings. They are ordered according to alphabetic conventions.	The variable `<school grade>` is an ordinal variable. Its values actually belong to definite categories and can be sorted. This variable can be: numerical, if its values range between `<0>` and `<20>`, textual, if its values are A, B, C, D, E and F.
Nominal	Values are discrete. They can be regrouped into categories. Caution Binary variables (variable with 2 distinct values only) are considered as nominal variables. They are the ones that can be used as target for classification predictive models	The variable `<zip code>` is a nominal variable. The set of values that this variable may assume are clearly distinct, non-ranked categories, although they happen to be represented by numbers. For example: `<10111>`, `<20500>` or `<90210>`. The variable `<eye color>` is a nominal variable. The set of values that this variable may assume are clearly distinct, non-ordered categories, and are represented by character strings. For example: `<blue>`, `<brown>`, `<black>`.
Textual Note These variables are currently not supported by Smart Predict, and are therefore excluded from the training of a predictive model.	A type of nominal variable containing phrases, sentences, or complete texts. Textual variables are used for text analyses.	For example the variable `<Bluetooth Headphones Customer Feedback>` is a textual variable. The values for this variable can be `<Durable cord, connect easy to phone and plug.>`, `<Great fit and great sound!>` or `<Great length and color. Super fast charging.>`.