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Level of Measurement

In statistics, the term "level of measurement" is broadly known as scale of measurement. It refers to the way by which a variable or a number is represented and categorized. Levels of measurement are basically types of data that are introduced by psychologist Stanley Smith Stevens. They have a certain types of properties which determine the use of statistical analyses.
There are four different types of level of measurements as discussed below:

  • Nominal
  • Ordinal
  • Interval
  • Ratio
Nominal Level of Measurement: Nominal scale measures the data which is qualitative in type. Variables measured on normal scale are the variable that assign category. These variables are not quantified.

For example:
  • Eye color - Blue, black, brown, green, hazel etc.
  • Gender - Male, female.
  • Religion - Hindu, Catholic, Muslim etc.
  • Race - African, Asian, European, Caucasian etc.
  • Marital status - Married, unmarried, divorced.
Ordinal Level of Measurement: Ordinal level of measurement classifies data into ranked categories. In this scale, the order of the various entities represent objects or events.

For example:
  • Grades - A+, A, B+, B, C+, C, etc.
  • Ranks - 1$^{st}$, 2$^{nd}$, 3$^{rd}$ etc.
  • Sizes - Small, medium, large, extra large etc.
Interval Level of Measurement: Ordinal data only measures order, but not the difference between two data. Interval level of measurement defines order as well as difference.

For example: High-class and medium-class income is categorized by ordinal level, while interval level of measurement also specifies the difference between the two incomes.

Interval level lacks true zero point. It does not specifies zero as reference point.

Ratio Level of Measurement:
Ratio scale does have absolute zero point. This is the reason it is used to define ratios. It is most used in the fields of engineering and science. It is also capable to represent central tendency in statistics. Any kind of variable that requires ratio can be represented at ratio level of measurement.

For Examples: Length, mass, weight, force energy, angle etc.

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