Variables can be measured at different levels of precision.  Various statistics have been invented to deal with each level of measurement.  In order to choose the proper statistics to examine data, we first have to figure out at what level each variable is measured.

 

We decide at which level we think a variable is measured by thinking about its categories.  We try to think of how the categories are related to each other and what patterns we can find.  Sometimes the categories are numbers, sometimes they are words.  Sometimes the categories have an inherent order to them, sometimes they do not.[1]

 

All data should not be analyzed the same way statistically because the entities represented by the numbers are different. For this reason, the researcher needs to know the level of data measurement represented by the numbers being analyzed.

 

Knowing the level of measurement helps you decide how to interpret the data from that variable. Knowing the level of measurement helps you decide what statistical analysis is appropriate on the values that were assigned.

 

The level of measurement of a variable in mathematics and statistics is a classification that is used to describe the nature of information contained within numbers assigned to objects and, therefore, within the variable. The levels were proposed by Stanley Smith Stevens in his 1946 article “On the theory of scales of measurement”.[2]

 

The correct level of measurement allows the researcher to apply the appropriate data analysis on the gathered data.

 

Stevens proposed four levels of measurement:

1. Nominal
2. Ordinal
3. Interval
4. Ratio

 

Level	Are Names	Inherent Order  (More to Less or Higher to Lower)	Numbers With Equal Intervals Between Them	Numbers With A Theoretical Zero Point
Nominal Level	X
Ordinal Level	X	X
Interval Level	X	X	X
Ratio Level	X	X	X	X

Table 1: Levels of measurement[3]