# (Machine|Statistical) Learning - (Predictor|Feature|Regressor|Characteristic) - (Independent|Explanatory) Variable (X)

A Independent variable is a variable used in supervised analysis in order to predict an outcome variable.

It's also known as:

• Predictor
• Input variable,
• Regressors,
• Manipulated variable,
• Characteristic
• Control variable
• Controlled variable
• Observed variable
• Explanatory variable
• Exposure variable

## 3 - Independent variable

In statistics, a predictor is well known as an independent variable (IV). It does not depend of the experimentational procedure and is more generally:

• a description of the characteristics of a group.
• better known as the manipulation, the treatment or conditions.

## 4 - Quasi-independent

A Quasi-independent variable is a variable that can not be random assigned (example: concussions, gender, Sexual orientation) .

Since the independent variable does not involve random and representative sampling, arguments about causality are not as strong

## 5 - Type

### 5.1 - Categorical

Some predictors are not quantitative but are qualitative, taking a discrete set of values.

These are also called:

• categorical predictors

Example:

• gender,
• student (student status),
• status (marital status)