## Classifying Variables as Quantitative or Qualitative

Data in samples represent variables which are used to statistically analyze patterns.

For example, a sample of clinic patients would contain a list of their weight values. In this case weight is the variable.

### Quantitative or Qualitative

All variables are either quantitative or qualitative based on the type of values they assume.

#### Quantitative

These variables, weight for example, assume numeric values and are typically used in math operations such as using a person’s weight to produce a BMI index value.

Quantitative variables are further distinguished by how many values they assume – whether they are discrete or continuous.

Discrete quantitative variables, such as a patient’s number of limbs in an amputee clinic – each person can only have four limbs.

Continuous variables are the most common type of quantitative variables because they receive an unlimited number of numeric values.

#### Qualitative

Variables which receive non-numeric values, such as categories like race or religion are qualitative in nature.

Due to the nature of the values not being numeric, math operations are not performed on these values, but are usually aggregated within reports.