# Statistical data types

Statistical data types are the categories of data used in statistics.

Numerical data, also known as quantitative data, consists of discrete or continuous data. Discrete numerical data are values that can be counted, such as a quantity; for example, the number of heads in 10 coin flips or the number of correct answers on a test. Continuous numbers are measurements in which the value may fall in between any two other values; for example, the speed of a car or a volume of water.

A car that travels from 0 to 60mph reaches all possible speeds between 0 and 60mph, which makes speed data continuous. Whereas the number of laps a car has taken on a racetrack increments by one each time, thus the number of laps is never between, for example, 1 and 2, and thus "number of laps" is a discrete value.

Categorical data, also known as qualitative data, consists of data which describes characteristics and does not have a mathematical meaning. For example: Gender, color, and favorite food are all types of categorical data. Though numbers can be assigned to categorical data, it is not valid to compare those numbers mathematically.

Ordinal data consists of a mix of categorical and numerical data, where the data fall into numerical categories. For example: a 5-points scale for product reviews is ordinal because each category is numeric and can be compared (e.g. to get an average rating).

## Broader Topics Related to Statistical data types

### Statistics

The analysis of numerical data

### Data

Facts, statistics, and references to information