Statistics - Sample (Variable | Attribute | Feature)

Card Puncher Data Processing


A (statistician|data miner) studying a population would be interested in collecting information about different characteristics of the subject (like their length, or weight, or age) in a sample. Those characteristics are called variables.

In a database, they are just columns.

They can take on multiple values. In contrast, a constant has only one value

A variable have:

In mathematics, variables are listed among the arguments that the function takes.

Data Type

Variables (of an instance) are of two types:

  • discrete (called nominal, categorical or qualitative)
  • or continuous (called numeric, numerical or quantitative).

and have 4 levels


When a characteristic can be neatly placed into well-defined groups, or categories that do not depend on order, it is called a categorical variable (some statisticians use the word qualitative).


When we are interested in the total number of each species of tortoise, or how many individuals there are per square kilometre. This type of variable is called numerical (or quantitative).

See Number - Collection


Type of attribute Type of model Description
independent variable (predictors|feature) supervised Predictors that affect a given outcome
dependent variable (outcome,…) supervised outcome that are affected by predictors
descriptors (unsupervised|descriptive) Items of information being analysed for natural groupings or associations.

Variable Name Glossary

Dependent variable Independent variable
Dependent Independent
Outcome Predictor


Missing Value

see Data Mining - (Missing Value|Not Available) NA

Case id

A Case Id identifies uniquely each record in order to help with model repeatability.

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