Interval Level, Ordinal Level

An example of an ordinal level variable is social class:

 

Choose the social class that best describes you.

  1. Lower class
  2. Working class
  3. Middle class
  4. Upper class

 

A researcher analyzing the responses could rank the responders in general order of how much money they make.

 

A piece of information that is not embedded in ordinal-level data measurement is relative difference between the data. For example, how much more money does a working class person make over the lower class, or upper class over working class. We can not say for certain how much more money upper class makes over middle class or if the difference between all four classes shown is the same.

 

Additional examples of ordinal-level data measurement include: Fortune 50 most admired companies, satisfaction index, etc.

 

Because nominal and ordinal data are often derived from imprecise measurements such as demographic questions, the categorization of people or objects, or the ranking of items, nominal and ordinal data are nonmetric data and are sometimes referred to as qualitative data.

Interval Level

Similar to ordinal-level data measurement, interval-level data is one in which the distances between consecutive attributes have meaning and the data are always numerical. Differences between arbitrary pairs of measurements can be meaningfully compared. Operations such as averaging and subtraction are therefore meaningful, but addition is not, and a zero point on the scale is arbitrary; negative values can be used. Variables measured at the interval level are called interval variables.[1]

 

The distances represented by the differences between consecutive numbers are equal; that is, interval data have equal intervals.

 

An example of interval-level measurement is Fahrenheit temperature. The difference between 30 degrees and 40 degrees represents the same temperature difference as the difference between 80 degrees and 90 degrees. This is because each 10 degree interval has the same physical meaning.

 

With Interval-level data, converting the units from one measurement to another involves multiplying by some factor, a, and adding another factor, b, such that y = b + ax. For example: Fahrenheit = 32 + (9/5)*Centigrade

 



[1] http://en.wikipedia.org/wiki/Level_of_measurement